WorldWideScience

Sample records for reservoir release forecast

  1. Energy optimization through probabilistic annual forecast water release technique for major storage hydroelectric reservoir

    International Nuclear Information System (INIS)

    Abdul Bahari Othman; Mohd Zamri Yusoff

    2006-01-01

    One of the important decisions to be made by the management of hydroelectric power plant associated with major storage reservoir is to determine the best turbine water release decision for the next financial year. The water release decision enables firm energy generated estimation for the coming financial year to be done. This task is usually a simple and straightforward task provided that the amount of turbine water release is known. The more challenging task is to determine the best water release decision that is able to resolve the two conflicting operational objectives which are minimizing the drop of turbine gross head and maximizing upper reserve margin of the reservoir. Most techniques from literature emphasize on utilizing the statistical simulations approach. Markovians models, for example, are a class of statistical model that utilizes the past and the present system states as a basis for predicting the future [1]. This paper illustrates that rigorous solution criterion can be mathematically proven to resolve those two conflicting operational objectives. Thus, best water release decision that maximizes potential energy for the prevailing natural inflow is met. It is shown that the annual water release decision shall be made in such a manner that annual return inflow that has return frequency smaller than critical return frequency (f c ) should not be considered. This criterion enables target turbine gross head to be set to the well-defined elevation. In the other words, upper storage margin of the reservoir shall be made available to capture magnitude of future inflow that has return frequency greater than or equal to f c. A case study is shown to demonstrate practical application of the derived mathematical formulas

  2. Probing magma reservoirs to improve volcano forecasts

    Science.gov (United States)

    Lowenstern, Jacob B.; Sisson, Thomas W.; Hurwitz, Shaul

    2017-01-01

    When it comes to forecasting eruptions, volcano observatories rely mostly on real-time signals from earthquakes, ground deformation, and gas discharge, combined with probabilistic assessments based on past behavior [Sparks and Cashman, 2017]. There is comparatively less reliance on geophysical and petrological understanding of subsurface magma reservoirs.

  3. Inflow forecasting using Artificial Neural Networks for reservoir operation

    Directory of Open Access Journals (Sweden)

    C. Chiamsathit

    2016-05-01

    Full Text Available In this study, multi-layer perceptron (MLP artificial neural networks have been applied to forecast one-month-ahead inflow for the Ubonratana reservoir, Thailand. To assess how well the forecast inflows have performed in the operation of the reservoir, simulations were carried out guided by the systems rule curves. As basis of comparison, four inflow situations were considered: (1 inflow known and assumed to be the historic (Type A; (2 inflow known and assumed to be the forecast (Type F; (3 inflow known and assumed to be the historic mean for month (Type M; and (4 inflow is unknown with release decision only conditioned on the starting reservoir storage (Type N. Reservoir performance was summarised in terms of reliability, resilience, vulnerability and sustainability. It was found that Type F inflow situation produced the best performance while Type N was the worst performing. This clearly demonstrates the importance of good inflow information for effective reservoir operation.

  4. Use of Operational Climate Forecasts in Reservoir Management and Operation

    Science.gov (United States)

    Arumugam, S.; Lall, U.

    2005-12-01

    Seasonal streamflow forecasts contingent on climate information are essential for short-term planning and for setting up contingency measures during extreme years. Similarly, monthly updates of streamflow forecasts are useful in quantifying surplus and shortfall in addressing the change in streamflow potential during the season. In this study, an operational streamflow forecasts for managing the Angat Reservoir System, Philippines, is developed using the precipitation forecasts from Atmospheric General Circulation Models (AGCM) that are forced by persisted Sea Surface Temperature (SST) conditions. The methodology employs principal components regression (PCR) to downscale the AGCM predicted precipitation fields to monthly streamflow forecasts. By performing retrospective analyses that combines streamflow forecasts with a dynamic water allocation model, we show that use of updated climate forecasts in reservoir operation results in increased reservoir system yields in comparison to using the seasonal streamflow forecasts alone. Revising the reservoir operation strategy based on updated streamflow forecasts is particularly critical in hydropower systems, since the increased yields from reduced spillage could be effectively utilized for power generation during above-normal inflow years. Further, analyzing the system performance under different scenarios of storage and demand, we show that the utility of climate information based reservoir inflow forecasts is more pronounced for systems with low storage to demand ratio.

  5. Uncertainty Assessment: Reservoir Inflow Forecasting with Ensemble Precipitation Forecasts and HEC-HMS

    Directory of Open Access Journals (Sweden)

    Sheng-Chi Yang

    2014-01-01

    Full Text Available During an extreme event, having accurate inflow forecasting with enough lead time helps reservoir operators decrease the impact of floods downstream. Furthermore, being able to efficiently operate reservoirs could help maximize flood protection while saving water for drier times of the year. This study combines ensemble quantitative precipitation forecasts and a hydrological model to provide a 3-day reservoir inflow in the Shihmen Reservoir, Taiwan. A total of six historical typhoons were used for model calibration, validation, and application. An understanding of cascaded uncertainties from the numerical weather model through the hydrological model is necessary for a better use for forecasting. This study thus conducted an assessment of forecast uncertainty on magnitude and timing of peak and cumulative inflows. It found that using the ensemble-mean had less uncertainty than randomly selecting individual member. The inflow forecasts with shorter length of cumulative time had a higher uncertainty. The results showed that using the ensemble precipitation forecasts with the hydrological model would have the advantage of extra lead time and serve as a valuable reference for operating reservoirs.

  6. Monthly reservoir inflow forecasting using a new hybrid SARIMA ...

    Indian Academy of Sciences (India)

    Department of Civil Engineering, Razi University, Kermanshah, Iran. ∗. Corresponding author. e-mail: bonakdari@yahoo.com. Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average ...

  7. Surrogate reservoir models for CSI well probabilistic production forecast

    Directory of Open Access Journals (Sweden)

    Saúl Buitrago

    2017-09-01

    Full Text Available The aim of this work is to present the construction and use of Surrogate Reservoir Models capable of accurately predicting cumulative oil production for every well stimulated with cyclic steam injection at any given time in a heavy oil reservoir in Mexico considering uncertain variables. The central composite experimental design technique was selected to capture the maximum amount of information from the model response with a minimum number of reservoir models simulations. Four input uncertain variables (the dead oil viscosity with temperature, the reservoir pressure, the reservoir permeability and oil sand thickness hydraulically connected to the well were selected as the ones with more impact on the initial hot oil production rate according to an analytical production prediction model. Twenty five runs were designed and performed with the STARS simulator for each well type on the reservoir model. The results show that the use of Surrogate Reservoir Models is a fast viable alternative to perform probabilistic production forecasting of the reservoir.

  8. Exploring the interactions between forecast accuracy, risk perception and perceived forecast reliability in reservoir operator's decision to use forecast

    Science.gov (United States)

    Shafiee-Jood, M.; Cai, X.

    2017-12-01

    Advances in streamflow forecasts at different time scales offer a promise for proactive flood management and improved risk management. Despite the huge potential, previous studies have found that water resources managers are often not willing to incorporate streamflow forecasts information in decisions making, particularly in risky situations. While low accuracy of forecasts information is often cited as the main reason, some studies have found that implementation of streamflow forecasts sometimes is impeded by institutional obstacles and behavioral factors (e.g., risk perception). In fact, a seminal study by O'Connor et al. (2005) found that risk perception is the strongest determinant of forecast use while managers' perception about forecast reliability is not significant. In this study, we aim to address this issue again. However, instead of using survey data and regression analysis, we develop a theoretical framework to assess the user-perceived value of streamflow forecasts. The framework includes a novel behavioral component which incorporates both risk perception and perceived forecast reliability. The framework is then used in a hypothetical problem where reservoir operator should react to probabilistic flood forecasts with different reliabilities. The framework will allow us to explore the interactions among risk perception and perceived forecast reliability, and among the behavioral components and information accuracy. The findings will provide insights to improve the usability of flood forecasts information through better communication and education.

  9. Financial Risk Reduction and Management of Water Reservoirs Using Forecasts: A Case for Pernambuco, Brazil

    Science.gov (United States)

    Kumar, I.; Josset, L.; e Silva, E. C.; Possas, J. M. C.; Asfora, M. C.; Lall, U.

    2017-12-01

    The financial health and sustainability, ensuring adequate supply, and adapting to climate are fundamental challenges faced by water managers. These challenges are worsened in semi-arid regions with socio-economic pressures, seasonal supply of water, and projected increase in intensity and frequency of droughts. Over time, probabilistic rainfall forecasts are improving and for water managers, it could be key in addressing the above challenges. Using forecasts can also help make informed decisions about future infrastructure. The study proposes a model to minimize cost of water supply (including cost of deficit) given ensemble forecasts. The model can be applied to seasonal to annual ensemble forecasts, to determine the least cost solution. The objective of the model is to evaluate the resiliency and cost associated to supplying water. A case study is conducted in one of the largest reservoirs (Jucazinho) in Pernambuco state, Brazil, and four other reservoirs, which provide water to nineteen municipalities in the Jucazinho system. The state has been in drought since 2011, and the Jucazinho reservoir, has been empty since January 2017. The importance of climate adaptation along with risk management and financial sustainability are important to the state as it is extremely vulnerable to droughts, and has seasonal streamflow. The objectives of the case study are first, to check if streamflow forecasts help reduce future supply costs by comparing k-nearest neighbor ensemble forecasts with a fixed release policy. Second, to determine the value of future infrastructure, a new source of supply from Rio São Francisco, considered to mitigate drought conditions. The study concludes that using forecasts improve the supply and financial sustainability of water, by reducing cost of failure. It also concludes that additional infrastructure can help reduce the risks of failure significantly, but does not guarantee supply during prolonged droughts like the one experienced

  10. Daily reservoir inflow forecasting combining QPF into ANNs model

    Science.gov (United States)

    Zhang, Jun; Cheng, Chun-Tian; Liao, Sheng-Li; Wu, Xin-Yu; Shen, Jian-Jian

    2009-01-01

    Daily reservoir inflow predictions with lead-times of several days are essential to the operational planning and scheduling of hydroelectric power system. The demand for quantitative precipitation forecasting (QPF) is increasing in hydropower operation with the dramatic advances in the numerical weather prediction (NWP) models. This paper presents a simple and an effective algorithm for daily reservoir inflow predictions which solicits the observed precipitation, forecasted precipitation from QPF as predictors and discharges in following 1 to 6 days as predicted targets for multilayer perceptron artificial neural networks (MLP-ANNs) modeling. An improved error back-propagation algorithm with self-adaptive learning rate and self-adaptive momentum coefficient is used to make the supervised training procedure more efficient in both time saving and search optimization. Several commonly used error measures are employed to evaluate the performance of the proposed model and the results, compared with that of ARIMA model, show that the proposed model is capable of obtaining satisfactory forecasting not only in goodness of fit but also in generalization. Furthermore, the presented algorithm is integrated into a practical software system which has been severed for daily inflow predictions with lead-times varying from 1 to 6 days of more than twenty reservoirs operated by the Fujian Province Grid Company, China.

  11. Forecast Informed Reservoir Operations: Bringing Science and Decision-Makers Together to Explore Use of Hydrometeorological Forecasts to Support Future Reservoir Operations

    Science.gov (United States)

    Ralph, F. M.; Jasperse, J.

    2017-12-01

    Forecast Informed Reservoir Operations (FIRO) is a proposed strategy that is exploring inorporation of improved hydrometeorological forecasts of land-falling atmospheric rivers on the U.S. West Coast into reservoir operations. The first testbed for this strategy is Lake Mendocino, which is located in the East Fork of the 1485 mi2 Russian River Watershed in northern California. This project is guided by the Lake Mendocino FIRO Steering Committee (SC). The SC is an ad hoc committee that consists of water managers and scientists from several federal, state, and local agencies, and universities who have teamed to evaluate whether current or improved technology and scientific understanding can be utilized to improve water supply reliability, enhance flood mitigation and support recovery of listed salmon for the Russian River of northern California. In 2015, the SC created a detailed work plan, which included a Preliminary Viability Assessment, which has now been completed. The SC developed a vision that operational efficiency would be improved by using forecasts to inform decisions about releasing or storing water. FIRO would use available reservoir storage in an efficient manner by (1) better forecasting inflow (or lack of inflow) with enhanced technology, and (2) adapting operation in real time to meet the need for storage, rather than making storage available just in case it is needed. The envisioned FIRO strategy has the potential to simultaneously improve water supply reliability, flood protection, and ecosystem outcomes through a more efficient use of existing infrastructure while requiring minimal capital improvements in the physical structure of the dam. This presentation will provide an overview of the creation of the FIRO SC and how it operates, and describes the lessons learned through this partnership. Results in the FIRO Preliminary Viability Assessment will be summarized and next steps described.

  12. Real-time short-term forecast of water inflow into Bureyskaya reservoir

    Science.gov (United States)

    Motovilov, Yury

    2017-04-01

    model performance as compared to observed inflow data into the Bureya reservoir and high diagnostic potential of data-modeling system of the runoff formation. With the use of this system the following flowchart for short-range forecasting inflow into Bureyskoe reservoir and forecast correction technique using continuously updated hydrometeorological data has been developed: 1 - Daily renewal of weather observations and forecasts database via the Internet; 2 - Daily runoff calculation from the beginning of the current year to current date is conducted; 3 - Short-range (up to 7 days) forecast is generated based on weather forecast. The idea underlying the model assimilation of newly obtained hydro meteorological information to adjust short-range hydrological forecasts lies in the assumption of the forecast errors inertia. Then the difference between calculated and observed streamflow at the forecast release date is "scattered" with specific weights to calculated streamflow for the forecast lead time. During 2016 this forecasts method of the inflow into the Bureyskaya reservoir up to 7 days is tested in online mode. Satisfactory evaluated short-range inflow forecast success rate is obtained. Tests of developed method have shown strong sensitivity to the results of short-term precipitation forecasts.

  13. Multi-data reservoir history matching for enhanced reservoir forecasting and uncertainty quantification

    KAUST Repository

    Katterbauer, Klemens

    2015-04-01

    Reservoir simulations and history matching are critical for fine-tuning reservoir production strategies, improving understanding of the subsurface formation, and forecasting remaining reserves. Production data have long been incorporated for adjusting reservoir parameters. However, the sparse spatial sampling of this data set has posed a significant challenge for efficiently reducing uncertainty of reservoir parameters. Seismic, electromagnetic, gravity and InSAR techniques have found widespread applications in enhancing exploration for oil and gas and monitoring reservoirs. These data have however been interpreted and analyzed mostly separately, rarely exploiting the synergy effects that could result from combining them. We present a multi-data ensemble Kalman filter-based history matching framework for the simultaneous incorporation of various reservoir data such as seismic, electromagnetics, gravimetry and InSAR for best possible characterization of the reservoir formation. We apply an ensemble-based sensitivity method to evaluate the impact of each observation on the estimated reservoir parameters. Numerical experiments for different test cases demonstrate considerable matching enhancements when integrating all data sets in the history matching process. Results from the sensitivity analysis further suggest that electromagnetic data exhibit the strongest impact on the matching enhancements due to their strong differentiation between water fronts and hydrocarbons in the test cases.

  14. Redesigning reservoir compensation releases for ecological beenfit

    Science.gov (United States)

    Maynard, Carly

    2010-05-01

    River regulation is commonplace in England and much of the UK. Regulation for the purposes of public water supply causes flows downstream of a reservoir to be attenuated and the flow regime of the channel to be altered. The impact of channel impoundment on a small, upland UK river, has been assessed and methods for mitigation of ecological impacts explored. The method utilised a unique macroinvertebrate data set for pre- and post-impoundment periods to quantify the impact of Derwent Reservoir and the steady, continuous compensation release into the River Derwent, Northumberland. Impacts on the hydrological regime were also investigated and links drawn between changes in flow regime and changes in macroinvertebrate richness and diversity as a result of impoundment. In response to the claim that the impoundment has caused a change in flow regime and had deleterious effects on fish and macroinvertebrates, a compensation redesign tool (CRAB: Compensation Release Assessment at the Broad scale) was employed to design new compensation release regimes from the reservoir which account for the seasonal flow requirements of a number of key fish species. The impact of impoundment on the current flow regime was modelled and the impacts of predicted new regimes were predicted, using a 1D hydrodynamic model (HEC-RAS), as part of a modelling process known as CRAM (Compensation Release Assessment at the Meso-scale). Depth and velocity were the foci of the analysis as they are the two habitat requirements most well documented for the fish species in question, they could be modelled using HEC-RAS and they can act as surrogates for other habitat parameters such as temperature and substrate. The suitability of the depth and velocity combinations predicted using the HEC-RAS model were assessed using fuzzy-rule based modelling, which allowed the habitat quality of a given parameter combination to be quantified. Based on the results of the investigation it was concluded that there has

  15. Sub-seasonal-to-seasonal Reservoir Inflow Forecast using Bayesian Hierarchical Hidden Markov Model

    Science.gov (United States)

    Mukhopadhyay, S.; Arumugam, S.

    2017-12-01

    Sub-seasonal-to-seasonal (S2S) (15-90 days) streamflow forecasting is an emerging area of research that provides seamless information for reservoir operation from weather time scales to seasonal time scales. From an operational perspective, sub-seasonal inflow forecasts are highly valuable as these enable water managers to decide short-term releases (15-30 days), while holding water for seasonal needs (e.g., irrigation and municipal supply) and to meet end-of-the-season target storage at a desired level. We propose a Bayesian Hierarchical Hidden Markov Model (BHHMM) to develop S2S inflow forecasts for the Tennessee Valley Area (TVA) reservoir system. Here, the hidden states are predicted by relevant indices that influence the inflows at S2S time scale. The hidden Markov model also captures the both spatial and temporal hierarchy in predictors that operate at S2S time scale with model parameters being estimated as a posterior distribution using a Bayesian framework. We present our work in two steps, namely single site model and multi-site model. For proof of concept, we consider inflows to Douglas Dam, Tennessee, in the single site model. For multisite model we consider reservoirs in the upper Tennessee valley. Streamflow forecasts are issued and updated continuously every day at S2S time scale. We considered precipitation forecasts obtained from NOAA Climate Forecast System (CFSv2) GCM as predictors for developing S2S streamflow forecasts along with relevant indices for predicting hidden states. Spatial dependence of the inflow series of reservoirs are also preserved in the multi-site model. To circumvent the non-normality of the data, we consider the HMM in a Generalized Linear Model setting. Skill of the proposed approach is tested using split sample validation against a traditional multi-site canonical correlation model developed using the same set of predictors. From the posterior distribution of the inflow forecasts, we also highlight different system behavior

  16. Building Adjustable Pre-storm Reservoir Flood-control Release Rules

    Science.gov (United States)

    Yang, Shun-Nien; Chang, Li-Chiu; Chang, Fi-John; Hsieh, Cheng-Daw

    2017-04-01

    Typhoons hit Taiwan several times every year, which could cause serious flood disasters. Because mountainous terrains and steep landforms can rapidly accelerate the speed of flood flow during typhoon events, rivers cannot be a stable source of water supply. Reservoirs become the most effective floodwater storage facilities for alleviating flood damages in Taiwan. The pre-storm flood-control release can significantly increase reservoir storage capacity available to store floodwaters for reducing downstream flood damage, while the uncertainties of total forecasted rainfalls are very high in different stages of an oncoming typhoon, which may cause the risk of water shortage in the future. This study proposes adjustable pre-storm reservoir flood-control release rules in three designed operating stages with various hydrological conditions in the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, not only to reduce the risk of reservoir flood control and downstream flooding but also to consider water supply. The three operating stages before an oncoming typhoon are defined upon the timings when: (1) typhoon news is issued (3-7days before typhoon hit); (2) the sea warning is issued (2-4 days before typhoon hit); and (3) the land warning is issued (1-2 days before typhoon hit). We simulate 95 historical typhoon events with 3000 initial water levels and build some pre-storm flood-control release rules to adjust the amount of pre-release based on the total forecasted rainfalls at different operating stages. A great number of simulations (68.4 millions) are conducted to extract their major consequences and then build the adjustable pre-storm reservoir flood-control release rules. Accordingly, given a total forecasted rainfall and a water level, reservoir decision makers can easily identify the corresponding rule to tell the amount of pre-release in any stage. The results show that the proposed adjustable pre-release rules can effectively

  17. An Integrated Risk Approach for Assessing the Use of Ensemble Streamflow Forecasts in Hydroelectric Reservoir Operations

    Science.gov (United States)

    Lowry, T. S.; Wigmosta, M.; Barco, J.; Voisin, N.; Bier, A.; Coleman, A.; Skaggs, R.

    2012-12-01

    This paper presents an integrated risk approach using ensemble streamflow forecasts for optimizing hydro-electric power generation. Uncertainty in the streamflow forecasts are translated into integrated risk by calculating the deviation of an optimized release schedule that simultaneously maximizes power generation and environmental performance from release schedules that maximize the two objectives individually. The deviations from each target are multiplied by the probability of occurrence and then summed across all probabilities to get the integrated risk. The integrated risk is used to determine which operational scheme exposes the operator to the least amount of risk or conversely, what are the consequences of basing future operations on a particular prediction. Decisions can be made with regards to the tradeoff between power generation, environmental performance, and exposure to risk. The Hydropower Seasonal Concurrent Optimization for Power and Environment (HydroSCOPE) model developed at Sandia National Laboratories (SNL) is used to model the flow, temperature, and power generation and is coupled with the DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) optimization package to identify the maximum potential power generation, the maximum environmental performance, and the optimal operational scheme that maximizes both for each instance of the ensemble forecasts. The ensemble forecasts were developed in a collaborative effort between the Pacific Northwest National Laboratory (PNNL) and the University of Washington to develop an Enhanced Hydrologic Forecasting System (EHFS) that incorporates advanced ensemble forecasting approaches and algorithms, spatiotemporal datasets, and automated data acquisition and processing. Both the HydroSCOPE model and the EHFS forecast tool are being developed as part of a larger, multi-laboratory water-use optimization project funded through the US Department of Energy. The simulations were based on the

  18. Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

    Directory of Open Access Journals (Sweden)

    S. W. D. Turner

    2017-09-01

    Full Text Available Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made – namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

  19. Complex relationship between seasonal streamflow forecast skill and value in reservoir operations

    Science.gov (United States)

    Turner, Sean W. D.; Bennett, James C.; Robertson, David E.; Galelli, Stefano

    2017-09-01

    Considerable research effort has recently been directed at improving and operationalising ensemble seasonal streamflow forecasts. Whilst this creates new opportunities for improving the performance of water resources systems, there may also be associated risks. Here, we explore these potential risks by examining the sensitivity of forecast value (improvement in system performance brought about by adopting forecasts) to changes in the forecast skill for a range of hypothetical reservoir designs with contrasting operating objectives. Forecast-informed operations are simulated using rolling horizon, adaptive control and then benchmarked against optimised control rules to assess performance improvements. Results show that there exists a strong relationship between forecast skill and value for systems operated to maintain a target water level. But this relationship breaks down when the reservoir is operated to satisfy a target demand for water; good forecast accuracy does not necessarily translate into performance improvement. We show that the primary cause of this behaviour is the buffering role played by storage in water supply reservoirs, which renders the forecast superfluous for long periods of the operation. System performance depends primarily on forecast accuracy when critical decisions are made - namely during severe drought. As it is not possible to know in advance if a forecast will perform well at such moments, we advocate measuring the consistency of forecast performance, through bootstrap resampling, to indicate potential usefulness in storage operations. Our results highlight the need for sensitivity assessment in value-of-forecast studies involving reservoirs with supply objectives.

  20. Uncertainties in reservoir performance forecasts; Estimativa de incertezas na previsao de desempenho de reservatorios

    Energy Technology Data Exchange (ETDEWEB)

    Loschiavo, Roberto

    1999-07-01

    Project economic evaluation as well as facilities design for oil exploration is, in general based on production forecast. Since production forecast depends on several parameters that are not completely known, one should take a probabilistic approach for reservoir modeling and numerical flow simulation. In this work, we propose a procedure to estimate probabilistic production forecast profiles based on the decision tree technique. The most influencing parameters of a reservoir model are identified identified and combined to generate a number of realizations of the reservoirs. The combination of each branch of the decision tree defines the probability associated to each reservoir model. A computer program was developed to automatically generate the reservoir models, submit them to the numerical simulator, and process the results. Parallel computing was used to improve the performance of the procedure. (author)

  1. Forecast on Water Locking Damage of Low Permeable Reservoir with Quantum Neural Network

    Science.gov (United States)

    Zhao, Jingyuan; Sun, Yuxue; Feng, Fuping; Zhao, Fulei; Sui, Dianjie; Xu, Jianjun

    2018-01-01

    It is of great importance in oil-gas reservoir protection to timely and correctly forecast the water locking damage, the greatest damage for low permeable reservoir. An analysis is conducted on the production mechanism and various influence factors of water locking damage, based on which a quantum neuron is constructed based on the information processing manner of a biological neuron and the principle of quantum neural algorithm, besides, the quantum neural network model forecasting the water locking of the reservoir is established and related software is also made to forecast the water locking damage of the gas reservoir. This method has overcome the defects of grey correlation analysis that requires evaluation matrix analysis and complicated operation. According to the practice in Longxi Area of Daqing Oilfield, this method is characterized by fast operation, few system parameters and high accuracy rate (the general incidence rate may reach 90%), which can provide reliable support for the protection technique of low permeable reservoir.

  2. Reservoir Management using seasonal forecasts in Lake Kariba and Lake Kahora Bassa: Initial results and plans

    CSIR Research Space (South Africa)

    Muchuru, S

    2012-06-01

    Full Text Available Seasonal forecasting as a tool to improve on reservoir management in Zimbabwe is presented. The focus of the talk is on predicting rainfall extremes over the Lake Kariba catchments. The forecast systems to do the predictions and the levels of skill...

  3. Influence of environmental factors on mercury release in hydroelectric reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    Morrison, K.; Therien, N.

    1991-04-01

    Due to increased mercury concentrations in fish in hydro-electric reservoirs after flooding, a study was carried out to evaluate the release and transformation of mercury due to vegetation and soil flooded as a result of reservoir creation. Samples of vegetation and soils were immersed in water and concentrations of total mercury, methylmercury and nutrients were followed. The effects of anoxia, pH and temperature on release and transformation were examined. An existing dynamic model of decomposition of flooded materials in reservoirs was modified to include mercury release and transformation, and was calibrated to the experimental data. Amounts of mercury released by the different substrates was of the same order of magnitude. Tree species contributed to the greatest amounts of methylmercury per unit biomass, but the biomass used for these was twigs and foliage. Soil released significant amounts of mercury, but methylation was very low. The model was able to fit well for all substrates except lichen. The model can be adapted to proposed reservoirs to predict nutrient and mecury release and transformation. 175 refs., 38 figs., 38 tabs.

  4. Application of the Fokker-Plank-Kolmogorov equation for affluence forecast to hydropower reservoirs (Betania Case)

    International Nuclear Information System (INIS)

    Dominguez Calle, Efrain Antonio

    2004-01-01

    This paper shows a modeling technique to forecast probability density curves for the flows that represent the monthly affluence to hydropower reservoirs. Briefly, the factors that require affluence forecast in terms of probabilities, the ranges of existing forecast methods as well as the contradiction between those techniques and the real requirements of decision-making procedures are pointed out. The mentioned contradiction is resolved applying the Fokker-Planck-Kolmogorov equation that describes the time evolution of a stochastic process that can be considered as markovian. We show the numerical scheme for this equation, its initial and boundary conditions, and its application results in the case of Betania's reservoir

  5. Wind field forecast for accidental release of radiative materials

    International Nuclear Information System (INIS)

    Kang Ling; Chen Jiayi; Cai Xuhui

    2003-01-01

    A meso-scale wind field forecast model was designed for emergency environmental assessment in case of accidental release of radiative materials from a nuclear power station. Actual practice of the model showed that it runs fast, has wind field prediction function, and the result given is accurate. With meteorological data collected from weather stations, and pre-treated by a wind field diagnostic model, the initial wind fields at different times were inputted as initial values and assimilation fields for the forecasting model. The model, in turn, worked out to forecast meso-scale wind field of 24 hours in a horizontal domain of 205 km x 205 km. And then, the diagnostic model was employed again with the forecasting data to obtain more detail information of disturbed wind field by local terrain in a smaller domain of 20.5 km x 20.5 km, of which the nuclear power station is at the center. Using observation data in January, April, July and October of 1996 over the area of Hangzhou Bay, wind fields in these 4 months were simulated by different assimilation time and number of the weather stations for a sensitive test. Results indicated that the method used here has increased accuracy of the forecasted wind fields. And incorporating diagnostic method with the wind field forecast model has greatly increased efficiency of the wind field forecast for the smaller domain. This model and scheme have been used in Environmental Consequence Assessment System of Nuclear Accident in Qinshan Area

  6. Developing reservoir monthly inflow forecasts using artificial intelligence and climate phenomenon information

    Science.gov (United States)

    Yang, Tiantian; Asanjan, Ata Akbari; Welles, Edwin; Gao, Xiaogang; Sorooshian, Soroosh; Liu, Xiaomang

    2017-04-01

    Reservoirs are fundamental human-built infrastructures that collect, store, and deliver fresh surface water in a timely manner for many purposes. Efficient reservoir operation requires policy makers and operators to understand how reservoir inflows are changing under different hydrological and climatic conditions to enable forecast-informed operations. Over the last decade, the uses of Artificial Intelligence and Data Mining [AI & DM] techniques in assisting reservoir streamflow subseasonal to seasonal forecasts have been increasing. In this study, Random Forest [RF), Artificial Neural Network (ANN), and Support Vector Regression (SVR) are employed and compared with respect to their capabilities for predicting 1 month-ahead reservoir inflows for two headwater reservoirs in USA and China. Both current and lagged hydrological information and 17 known climate phenomenon indices, i.e., PDO and ENSO, etc., are selected as predictors for simulating reservoir inflows. Results show (1) three methods are capable of providing monthly reservoir inflows with satisfactory statistics; (2) the results obtained by Random Forest have the best statistical performances compared with the other two methods; (3) another advantage of Random Forest algorithm is its capability of interpreting raw model inputs; (4) climate phenomenon indices are useful in assisting monthly or seasonal forecasts of reservoir inflow; and (5) different climate conditions are autocorrelated with up to several months, and the climatic information and their lags are cross correlated with local hydrological conditions in our case studies.

  7. Ensemble Flow Forecasts for Risk Based Reservoir Operations of Lake Mendocino in Mendocino County, California: A Framework for Objectively Leveraging Weather and Climate Forecasts in a Decision Support Environment

    Science.gov (United States)

    Delaney, C.; Hartman, R. K.; Mendoza, J.; Whitin, B.

    2017-12-01

    Forecast informed reservoir operations (FIRO) is a methodology that incorporates short to mid-range precipitation and flow forecasts to inform the flood operations of reservoirs. The Ensemble Forecast Operations (EFO) alternative is a probabilistic approach of FIRO that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, release decisions are made to manage forecasted risk of reaching critical operational thresholds. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC. The ESP hindcast was developed using Global Ensemble Forecast System version 10 precipitation reforecasts processed with the Hydrologic Ensemble Forecast System to generate daily reforecasts of 61 flow ensemble members for a 15-day forecast horizon. Model simulation results demonstrate that the EFO alternative may improve water supply reliability for Lake Mendocino yet not increase flood risk for downstream areas. The developed operations framework can directly leverage improved skill in the second week of the forecast and is extendable into the S2S time domain given the demonstration of improved skill through a reliable reforecast of adequate historical duration and consistent with operationally available numerical weather predictions.

  8. Ensemble seasonal forecast of extreme water inflow into a large reservoir

    Directory of Open Access Journals (Sweden)

    A. N. Gelfan

    2015-06-01

    Full Text Available An approach to seasonal ensemble forecast of unregulated water inflow into a large reservoir was developed. The approach is founded on a physically-based semi-distributed hydrological model ECOMAG driven by Monte-Carlo generated ensembles of weather scenarios for a specified lead-time of the forecast (3 months ahead in this study. Case study was carried out for the Cheboksary reservoir (catchment area is 374 000 km2 located on the middle Volga River. Initial watershed conditions on the forecast date (1 March for spring freshet and 1 June for summer low-water period were simulated by the hydrological model forced by daily meteorological observations several months prior to the forecast date. A spatially distributed stochastic weather generator was used to produce time-series of daily weather scenarios for the forecast lead-time. Ensemble of daily water inflow into the reservoir was obtained by driving the ECOMAG model with the generated weather time-series. The proposed ensemble forecast technique was verified on the basis of the hindcast simulations for 29 spring and summer seasons beginning from 1982 (the year of the reservoir filling to capacity to 2010. The verification criteria were used in order to evaluate an ability of the proposed technique to forecast freshet/low-water events of the pre-assigned severity categories.

  9. Risk Analysis of Multipurpose Reservoir Real-time Operation based on Probabilistic Hydrologic Forecasting

    Science.gov (United States)

    Liu, P.

    2011-12-01

    Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based probabilistic hydrologic forecasting, which outputs a lot of inflow scenarios or traces, does well in depicting the inflow not only the marginal distribution but also their corrections. This motivates us to analyze the reservoir operating risk by inputting probabilistic hydrologic forecasting into reservoir real-time operation. The proposed procedure involves: (1) based upon the Bayesian inference, two alternative techniques, the generalized likelihood uncertainty estimation (GLUE) and Markov chain Monte Carlo (MCMC), are implemented for producing probabilistic hydrologic forecasting, respectively, (2) the reservoir risk is defined as the ratio of the number of traces that excessive (or below) the critical value to the total number of traces, and (3) a multipurpose reservoir operation model is build to produce Pareto solutions for trade-offs between risks and profits with the inputted probabilistic hydrologic forecasting. With a case study of the China's Three Gorges Reservoir, it is found that the reservoir real-time operation risks can be estimated and minimized based on the proposed methods, and this is great potential benefit in decision and choosing the most realistic one.

  10. Application of probabilistic hydrologic forecasting for risk analysis of multipurpose reservoir real-time operation

    Science.gov (United States)

    Liu, P.

    2012-12-01

    Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based probabilistic hydrologic forecasting depicts the inflow not only the marginal distributions but also their corrections by producing inflow scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasting inputs. The proposed procedure involves: (1) based upon the Bayesian inference, the Markov Chain Monte Carlo (MCMC) is implemented to produce ensemble-based probabilistic hydrologic forecasting, (2) the reservoir risk is defined as the ratio of the number of scenarios that excessive the critical value to the total number of scenarios, (3) a multipurpose reservoir operation model is built and solved using scenario optimization to produce Pareto solutions for trade-offs between risks and profits. With a case study of the China's Three Gorges Reservoir (TGR) for the 2010 and 2012 floods, it is found that the reservoir real-time operation risks can be estimated directly and minimized based on the proposed methods, and is easy of implementation by the reservoir operators.

  11. Evaluating National Weather Service Seasonal Forecast Products in Reservoir Operation Case Studies

    Science.gov (United States)

    Nielson, A.; Guihan, R.; Polebistki, A.; Palmer, R. N.; Werner, K.; Wood, A. W.

    2014-12-01

    Forecasts of future weather and streamflow can provide valuable information for reservoir operations and water management. A challenge confronting reservoir operators today is how to incorporate both climate and streamflow products into their operations and which of these forecast products are most informative and useful for optimized water management. This study incorporates several reforecast products provided by the Colorado Basin River Forecast Center (CBRFC) which allows a complete retrospective analysis of climate forecasts, resulting in an evaluation of each product's skill in the context of water resources management. The accuracy and value of forecasts generated from the Climate Forecast System version 2 (CFSv2) are compared to the accuracy and value of using an Ensemble Streamflow Predictions (ESP) approach. Using the CFSv2 may offer more insight when responding to climate driven extremes than the ESP approach because the CFSv2 incorporates a fully coupled climate model into its forecasts rather than using all of the historic climate record as being equally probable. The role of forecast updating frequency will also be explored. Decision support systems (DSS) for both Salt Lake City Parley's System and the Snohomish County Public Utility Department's (SnoPUD) Jackson project will be used to illustrate the utility of forecasts. Both DSS include a coupled simulation and optimization model that will incorporate system constraints, operating policies, and environmental flow requirements. To determine the value of the reforecast products, performance metrics meaningful to the managers of each system are to be identified and quantified. Without such metrics and awareness of seasonal operational nuances, it is difficult to identify forecast improvements in meaningful ways. These metrics of system performance are compared using the different forecast products to evaluate the potential benefits of using CFSv2 seasonal forecasts in systems decision making.

  12. Seasonal Forecasting of Reservoir Inflow for the Segura River Basin, Spain

    Science.gov (United States)

    de Tomas, Alberto; Hunink, Johannes

    2017-04-01

    A major threat to the agricultural sector in Europe is an increasing occurrence of low water availability for irrigation, affecting the local and regional food security and economies. Especially in the Mediterranean region, such as in the Segura river basin (Spain), drought epidodes are relatively frequent. Part of the irrigation water demand in this basin is met by a water transfer from the Tagus basin (central Spain), but also in this basin an increasing pressure on the water resources has reduced the water available to be transferred. Currently, Drought Management Plans in these Spanish basins are in place and mitigate the impact of drought periods to some extent. Drought indicators that are derived from the available water in the storage reservoirs impose a set of drought mitigation measures. Decisions on water transfers are dependent on a regression-based time series forecast from the reservoir inflows of the preceding months. This user-forecast has its limitations and can potentially be improved using more advanced techniques. Nowadays, seasonal climate forecasts have shown to have increasing skill for certain areas and for certain applications. So far, such forecasts have not been evaluated in a seasonal hydrologic forecasting system in the Spanish context. The objective of this work is to develop a prototype of a Seasonal Hydrologic Forecasting System and compare this with a reference forecast. The reference forecast in this case is the locally used regression-based forecast. Additionally, hydrological simulations derived from climatological reanalysis (ERA-Interim) are taken as a reference forecast. The Spatial Processes in Hydrology model (SPHY - http://www.sphy.nl/) forced with the ECMWF- SFS4 (15 ensembles) Seasonal Forecast Systems is used to predict reservoir inflows of the upper basins of the Segura and Tagus rivers. The system is evaluated for 4 seasons with a forecasting lead time of 3 months. First results show that only for certain initialization

  13. Improving real-time inflow forecasting into hydropower reservoirs through a complementary modelling framework

    Science.gov (United States)

    Gragne, A. S.; Sharma, A.; Mehrotra, R.; Alfredsen, K.

    2015-08-01

    Accuracy of reservoir inflow forecasts is instrumental for maximizing the value of water resources and benefits gained through hydropower generation. Improving hourly reservoir inflow forecasts over a 24 h lead time is considered within the day-ahead (Elspot) market of the Nordic exchange market. A complementary modelling framework presents an approach for improving real-time forecasting without needing to modify the pre-existing forecasting model, but instead formulating an independent additive or complementary model that captures the structure the existing operational model may be missing. We present here the application of this principle for issuing improved hourly inflow forecasts into hydropower reservoirs over extended lead times, and the parameter estimation procedure reformulated to deal with bias, persistence and heteroscedasticity. The procedure presented comprises an error model added on top of an unalterable constant parameter conceptual model. This procedure is applied in the 207 km2 Krinsvatn catchment in central Norway. The structure of the error model is established based on attributes of the residual time series from the conceptual model. Besides improving forecast skills of operational models, the approach estimates the uncertainty in the complementary model structure and produces probabilistic inflow forecasts that entrain suitable information for reducing uncertainty in the decision-making processes in hydropower systems operation. Deterministic and probabilistic evaluations revealed an overall significant improvement in forecast accuracy for lead times up to 17 h. Evaluation of the percentage of observations bracketed in the forecasted 95 % confidence interval indicated that the degree of success in containing 95 % of the observations varies across seasons and hydrologic years.

  14. Improving inflow forecasting into hydropower reservoirs through a complementary modelling framework

    Science.gov (United States)

    Gragne, A. S.; Sharma, A.; Mehrotra, R.; Alfredsen, K.

    2014-10-01

    Accuracy of reservoir inflow forecasts is instrumental for maximizing the value of water resources and benefits gained through hydropower generation. Improving hourly reservoir inflow forecasts over a 24 h lead-time is considered within the day-ahead (Elspot) market of the Nordic exchange market. We present here a new approach for issuing hourly reservoir inflow forecasts that aims to improve on existing forecasting models that are in place operationally, without needing to modify the pre-existing approach, but instead formulating an additive or complementary model that is independent and captures the structure the existing model may be missing. Besides improving forecast skills of operational models, the approach estimates the uncertainty in the complementary model structure and produces probabilistic inflow forecasts that entrain suitable information for reducing uncertainty in the decision-making processes in hydropower systems operation. The procedure presented comprises an error model added on top of an un-alterable constant parameter conceptual model, the models being demonstrated with reference to the 207 km2 Krinsvatn catchment in central Norway. The structure of the error model is established based on attributes of the residual time series from the conceptual model. Deterministic and probabilistic evaluations revealed an overall significant improvement in forecast accuracy for lead-times up to 17 h. Season based evaluations indicated that the improvement in inflow forecasts varies across seasons and inflow forecasts in autumn and spring are less successful with the 95% prediction interval bracketing less than 95% of the observations for lead-times beyond 17 h.

  15. Hybrid Stochastic Forecasting Model for Management of Large Open Water Reservoir with Storage Function

    Science.gov (United States)

    Kozel, Tomas; Stary, Milos

    2017-12-01

    The main advantage of stochastic forecasting is fan of possible value whose deterministic method of forecasting could not give us. Future development of random process is described better by stochastic then deterministic forecasting. Discharge in measurement profile could be categorized as random process. Content of article is construction and application of forecasting model for managed large open water reservoir with supply function. Model is based on neural networks (NS) and zone models, which forecasting values of average monthly flow from inputs values of average monthly flow, learned neural network and random numbers. Part of data was sorted to one moving zone. The zone is created around last measurement average monthly flow. Matrix of correlation was assembled only from data belonging to zone. The model was compiled for forecast of 1 to 12 month with using backward month flows (NS inputs) from 2 to 11 months for model construction. Data was got ridded of asymmetry with help of Box-Cox rule (Box, Cox, 1964), value r was found by optimization. In next step were data transform to standard normal distribution. The data were with monthly step and forecast is not recurring. 90 years long real flow series was used for compile of the model. First 75 years were used for calibration of model (matrix input-output relationship), last 15 years were used only for validation. Outputs of model were compared with real flow series. For comparison between real flow series (100% successfully of forecast) and forecasts, was used application to management of artificially made reservoir. Course of water reservoir management using Genetic algorithm (GE) + real flow series was compared with Fuzzy model (Fuzzy) + forecast made by Moving zone model. During evaluation process was founding the best size of zone. Results show that the highest number of input did not give the best results and ideal size of zone is in interval from 25 to 35, when course of management was almost same for

  16. Production forecasting and economic evaluation of horizontal wells completed in natural fractured reservoirs

    International Nuclear Information System (INIS)

    Evans, R. D.

    1996-01-01

    A technique for optimizing recovery of hydrocarbons from naturally fractured reservoirs using horizontal well technology was proposed. The technique combines inflow performance analysis, production forecasting and economic considerations, and is based on material balance analysis and linear approximations of reservoir fluid properties as functions of reservoir pressure. An economic evaluation model accounting for the time value of cash flow, interest and inflation rates, is part of the package. Examples of using the technique have been demonstrated. The method is also applied to a gas well producing from a horizontal wellbore intersecting discrete natural fractures. 11 refs., 2 tabs,. 10 figs

  17. Stochastic nonlinear time series forecasting using time-delay reservoir computers: performance and universality.

    Science.gov (United States)

    Grigoryeva, Lyudmila; Henriques, Julie; Larger, Laurent; Ortega, Juan-Pablo

    2014-07-01

    Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay differential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We tackle some problems associated to the lack of task-universality for individually operating reservoirs and propose a solution based on the use of parallel arrays of time-delay reservoirs. Copyright © 2014 Elsevier Ltd. All rights reserved.

  18. Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

    Science.gov (United States)

    Lu, Mengqian; Lall, Upmanu; Robertson, Andrew W.; Cook, Edward

    2017-03-01

    Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short-term and long-term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. The issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real-world perspective and needs a suitable institutional environment.

  19. Real-time dynamic control of the Three Gorges Reservoir by coupling numerical weather rainfall prediction and flood forecasting

    DEFF Research Database (Denmark)

    Wang, Y.; Chen, H.; Rosbjerg, Dan

    2013-01-01

    In reservoir operation improvement of the accuracy of forecast flood inflow and extension of forecast lead-time can effectively be achieved by using rainfall forecasts from numerical weather predictions with a hydrological catchment model. In this study, the Regional Spectrum Model (RSM), which i...

  20. A Generalized Martingale Model of Streamflow Forecast Uncertainty Evolution and its Application in the Three Gorge Reservoir Operation

    Science.gov (United States)

    Zhao, J.; Zhao, T.

    2012-12-01

    Streamflow forecasts are dynamically updated in real-time, which leads to a process of forecast uncertainty evolution. Generally, forecast uncertainty reduces as time progresses and more hydrologic information becomes available. This process of forecasting and uncertainty updating can be described by the martingale model of forecast evolution (MMFE), which formulates the total forecast uncertainty of streamflow in one future period as the sum of forecast improvements in the intermediate periods. This study tests the basic assumptions of MMFE with the streamflow forecast data from the Three Gorge Reservoir and shows that 1) real-world forecasts can be biased and tend to underestimate the actual streamflow and 2) real-world forecast uncertainty can be non-Gaussian and heavy-tailed. Based on these statistical tests, this study incorporates the normal quantile transform (NQT) method and issues a generalized NQT-MMFE model to simulate biased and non-Gaussian forecast uncertainties. The simulated streamflow forecast is similar to the real-world forecast in terms of NSE, MAE, and RMSE, which illustrates the effectiveness of the NQT-MMFE model. The simulated forecasts are further applied to a Monte-Carlo experiment of the Three Gorge Reservoir re-operation. The results illustrate that NQT-MMFE model within a rolling horizon decision making framework can efficiently exploit forecast information and make more robust decisions. The real-time streamflow forecast of TGR in 2008

  1. Forecasting monthly inflow discharge of the Iffezheim reservoir using data-driven models

    Science.gov (United States)

    Zhang, Qing; Aljoumani, Basem; Hillebrand, Gudrun; Hoffmann, Thomas; Hinkelmann, Reinhard

    2017-04-01

    River stream flow is an essential element in hydrology study fields, especially for reservoir management, since it defines input into reservoirs. Forecasting this stream flow plays an important role in short or long-term planning and management in the reservoir, e.g. optimized reservoir and hydroelectric operation or agricultural irrigation. Highly accurate flow forecasting can significantly reduce economic losses and is always pursued by reservoir operators. Therefore, hydrologic time series forecasting has received tremendous attention of researchers. Many models have been proposed to improve the hydrological forecasting. Due to the fact that most natural phenomena occurring in environmental systems appear to behave in random or probabilistic ways, different cases may need a different methods to forecast the inflow and even a unique treatment to improve the forecast accuracy. The purpose of this study is to determine an appropriate model for forecasting monthly inflow to the Iffezheim reservoir in Germany, which is the last of the barrages in the Upper Rhine. Monthly time series of discharges, measured from 1946 to 2001 at the Plittersdorf station, which is located 6 km downstream of the Iffezheim reservoir, were applied. The accuracies of the used stochastic models - Fiering model and Auto-Regressive Integrated Moving Average models (ARIMA) are compared with Artificial Intelligence (AI) models - single Artificial Neural Network (ANN) and Wavelet ANN models (WANN). The Fiering model is a linear stochastic model and used for generating synthetic monthly data. The basic idea in modeling time series using ARIMA is to identify a simple model with as few model parameters as possible in order to provide a good statistical fit to the data. To identify and fit the ARIMA models, four phase approaches were used: identification, parameter estimation, diagnostic checking, and forecasting. An automatic selection criterion, such as the Akaike information criterion, is utilized

  2. Decline Curve Analysis for Production Forecast and Optimization of Liquid-Dominated Geothermal Reservoir

    Science.gov (United States)

    Hidayat, I.

    2016-09-01

    Power projects in the geothermal field has a long span of about 30 years. The power supply should be maintained at a certain value across a range of time. A geothermal field, however, has the characteristics of natural production decline with time. In a geothermal field, development of decline curve model of steam production is important for forecasting production decline in the future. This study was developed using decline curve by production data along 3 years liquid-dominated geothermal reservoir in Ulubelu field. Decline curve in geothermal field based on decline curve in petroleum industry. The decline curve was correlated by reservoir management in geothermal. The purposes of this study to get best match model decline curve and forecasting production in the future. Based on decline curve analysis by production data in Ulubelu field, the result model decline curve is exponential model. From the model, we can get the value of decline rate in the field is 9.4 %/year. Then, the formula of forecasting steam flow used exponent decline to forecast in the future. By using separated system cycle in Ulubelu field, the minimal steam flowrate towards turbine was 502018.4 ton/month. Based on formula of forecasting production and minimal steam flowrate, we can get the time make up wells to maintain steam supply for stability in generator power capacity.

  3. Real-time dynamic control of the Three Gorges Reservoir by coupling numerical weather rainfall prediction and flood forecasting

    DEFF Research Database (Denmark)

    Wang, Y.; Chen, H.; Rosbjerg, Dan

    2013-01-01

    In reservoir operation improvement of the accuracy of forecast flood inflow and extension of forecast lead-time can effectively be achieved by using rainfall forecasts from numerical weather predictions with a hydrological catchment model. In this study, the Regional Spectrum Model (RSM), which...... is developed by the Japan Meteorological Agency, was used to forecast rainfall with 5 days lead-time in the upper region of the Three Gorges Reservoir (TGR). A conceptual hydrological model, the Xinanjiang Model, has been set up to forecast the inflow flood of TGR by the Ministry of Water Resources Information...... Center. Here, the flood forecast model coupled with the rainfall forecast from RSM has been employed to carry out real-time dynamic control of the Flood Limiting Water Level (FLWL) of TGR in order to improve the hydropower generation without increasing the flood risk. Taking the flood events of the flood...

  4. Reservoir operation using El Niño forecasts-case study of Daule Peripa and Baba, Ecuador

    DEFF Research Database (Denmark)

    Gelati, Emiliano; Madsen, Henrik; Rosbjerg, Dan

    2014-01-01

    Reservoir operation is studied for the Daule Peripa and Baba system in Ecuador, where El Niño events cause anomalously heavy precipitation. Reservoir inflow is modelled by a Markov-switching model using El Niño-Southern Oscillation (ENSO) indices as input. Inflow is forecast using 9-month lead time...

  5. EMSE: Synergizing EM and seismic data attributes for enhanced forecasts of reservoirs

    KAUST Repository

    Katterbauer, Klemens

    2014-10-01

    New developments of electromagnetic and seismic techniques have recently revolutionized the oil and gas industry. Time-lapse seismic data is providing engineers with tools to more accurately track the dynamics of multi-phase reservoir fluid flows. With the challenges faced in distinguishing between hydrocarbons and water via seismic methods, the industry has been looking at electromagnetic techniques in order to exploit the strong contrast in conductivity between hydrocarbons and water. Incorporating this information into reservoir simulation is expected to considerably enhance the forecasting of the reservoir, hence optimizing production and reducing costs. Conventional approaches typically invert the seismic and electromagnetic data in order to transform them into production parameters, before incorporating them as constraints in the history matching process and reservoir simulations. This makes automatization difficult and computationally expensive due to the necessity of manual processing, besides the potential artifacts. Here we introduce a new approach to incorporate seismic and electromagnetic data attributes directly into the history matching process. To avoid solving inverse problems and exploit information in the dynamics of the flow, we exploit petrophysical transformations to simultaneously incorporate time lapse seismic and electromagnetic data attributes using different ensemble Kalman-based history matching techniques. Our simulation results show enhanced predictability of the critical reservoir parameters and reduce uncertainties in model simulations, outperforming with only production data or the inclusion of either seismic or electromagnetic data. A statistical test is performed to confirm the significance of the results. © 2014 Elsevier B.V. All rights reserved.

  6. A statistical data assimilation method for seasonal streamflow forecasting to optimize hydropower reservoir management in data-scarce regions

    Science.gov (United States)

    Arsenault, R.; Mai, J.; Latraverse, M.; Tolson, B.

    2017-12-01

    Probabilistic ensemble forecasts generated by the ensemble streamflow prediction (ESP) methodology are subject to biases due to errors in the hydrological model's initial states. In day-to-day operations, hydrologists must compensate for discrepancies between observed and simulated states such as streamflow. However, in data-scarce regions, little to no information is available to guide the streamflow assimilation process. The manual assimilation process can then lead to more uncertainty due to the numerous options available to the forecaster. Furthermore, the model's mass balance may be compromised and could affect future forecasts. In this study we propose a data-driven approach in which specific variables that may be adjusted during assimilation are defined. The underlying principle was to identify key variables that would be the most appropriate to modify during streamflow assimilation depending on the initial conditions such as the time period of the assimilation, the snow water equivalent of the snowpack and meteorological conditions. The variables to adjust were determined by performing an automatic variational data assimilation on individual (or combinations of) model state variables and meteorological forcing. The assimilation aimed to simultaneously optimize: (1) the error between the observed and simulated streamflow at the timepoint where the forecasts starts and (2) the bias between medium to long-term observed and simulated flows, which were simulated by running the model with the observed meteorological data on a hindcast period. The optimal variables were then classified according to the initial conditions at the time period where the forecast is initiated. The proposed method was evaluated by measuring the average electricity generation of a hydropower complex in Québec, Canada driven by this method. A test-bed which simulates the real-world assimilation, forecasting, water release optimization and decision-making of a hydropower cascade was

  7. Recently released EIA report presents international forecasting data

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-05-01

    This report presents information from the Energy Information Administration (EIA). Articles are included on international energy forecasting data, data on the use of home appliances, gasoline prices, household energy use, and EIA information products and dissemination avenues.

  8. A Forecasting Approach Combining Self-Organizing Map with Support Vector Regression for Reservoir Inflow during Typhoon Periods

    Directory of Open Access Journals (Sweden)

    Gwo-Fong Lin

    2016-01-01

    Full Text Available This study describes the development of a reservoir inflow forecasting model for typhoon events to improve short lead-time flood forecasting performance. To strengthen the forecasting ability of the original support vector machines (SVMs model, the self-organizing map (SOM is adopted to group inputs into different clusters in advance of the proposed SOM-SVM model. Two different input methods are proposed for the SVM-based forecasting method, namely, SOM-SVM1 and SOM-SVM2. The methods are applied to an actual reservoir watershed to determine the 1 to 3 h ahead inflow forecasts. For 1, 2, and 3 h ahead forecasts, improvements in mean coefficient of efficiency (MCE due to the clusters obtained from SOM-SVM1 are 21.5%, 18.5%, and 23.0%, respectively. Furthermore, improvement in MCE for SOM-SVM2 is 20.9%, 21.2%, and 35.4%, respectively. Another SOM-SVM2 model increases the SOM-SVM1 model for 1, 2, and 3 h ahead forecasts obtained improvement increases of 0.33%, 2.25%, and 10.08%, respectively. These results show that the performance of the proposed model can provide improved forecasts of hourly inflow, especially in the proposed SOM-SVM2 model. In conclusion, the proposed model, which considers limit and higher related inputs instead of all inputs, can generate better forecasts in different clusters than are generated from the SOM process. The SOM-SVM2 model is recommended as an alternative to the original SVR (Support Vector Regression model because of its accuracy and robustness.

  9. Advanced productivity forecast using petrophysical wireline data calibrated with MDT tests and numerical reservoir simulation

    Energy Technology Data Exchange (ETDEWEB)

    Andre, Carlos de [PETROBRAS, Rio de Janeiro, RJ (Brazil); Canas, Jesus A.; Low, Steven; Barreto, Wesley [Schlumberger, Houston, TX (United States)

    2004-07-01

    This paper describes an integrated and rigorous approach for viscous and middle oil reservoir productivity evaluation using petrophysical models calibrated with permeability derived from mini tests (Dual Packer) and Vertical Interference Tests (VIT) from open hole wire line testers (MDT SLB TM). It describes the process from Dual Packer Test and VIT pre-job design, evaluation via analytical and inverse simulation modeling, calibration and up scaling of petrophysical data into a numerical model, history matching of Dual Packer Tests and VIT with numerical simulation modeling. Finally, after developing a dynamic calibrated model, we perform productivity forecasts of different well configurations (vertical, horizontal and multilateral wells) for several deep offshore oil reservoirs in order to support well testing activities and future development strategies. The objective was to characterize formation static and dynamic properties early in the field development process to optimize well testing design, extended well test (EWT) and support the development strategies in deep offshore viscous oil reservoirs. This type of oil has limitations to flow naturally to surface and special lifting equipment is required for smooth optimum well testing/production. The integrated analysis gave a good overall picture of the formation, including permeability anisotropy and fluid dynamics. Subsequent analysis of different well configurations and lifting schemes allows maximizing formation productivity. The simulation and calibration results are compared to measured well test data. Results from this work shows that if the various petrophysical and fluid properties sources are integrated properly an accurate well productivity model can be achieved. If done early in the field development program, this time/knowledge gain could reduce the risk and maximize the development profitability of new blocks (value of the information). (author)

  10. A two-stage method of quantitative flood risk analysis for reservoir real-time operation using ensemble-based hydrologic forecasts

    Science.gov (United States)

    Liu, P.

    2013-12-01

    Quantitative analysis of the risk for reservoir real-time operation is a hard task owing to the difficulty of accurate description of inflow uncertainties. The ensemble-based hydrologic forecasts directly depict the inflows not only the marginal distributions but also their persistence via scenarios. This motivates us to analyze the reservoir real-time operating risk with ensemble-based hydrologic forecasts as inputs. A method is developed by using the forecast horizon point to divide the future time into two stages, the forecast lead-time and the unpredicted time. The risk within the forecast lead-time is computed based on counting the failure number of forecast scenarios, and the risk in the unpredicted time is estimated using reservoir routing with the design floods and the reservoir water levels of forecast horizon point. As a result, a two-stage risk analysis method is set up to quantify the entire flood risks by defining the ratio of the number of scenarios that excessive the critical value to the total number of scenarios. The China's Three Gorges Reservoir (TGR) is selected as a case study, where the parameter and precipitation uncertainties are implemented to produce ensemble-based hydrologic forecasts. The Bayesian inference, Markov Chain Monte Carlo, is used to account for the parameter uncertainty. Two reservoir operation schemes, the real operated and scenario optimization, are evaluated for the flood risks and hydropower profits analysis. With the 2010 flood, it is found that the improvement of the hydrologic forecast accuracy is unnecessary to decrease the reservoir real-time operation risk, and most risks are from the forecast lead-time. It is therefore valuable to decrease the avarice of ensemble-based hydrologic forecasts with less bias for a reservoir operational purpose.

  11. [Preparation and release mechanism of gestodene reservoir-type intravaginal rings].

    Science.gov (United States)

    Li, Chun-Xiao; Wang, Yan-Kun; Ning, Mei-Ying

    2014-03-01

    This study taking gestodene (GEST) as a model, investigated the factors affecting reservoir-type intravaginal ring (IVR)'s drug release. This paper reported a gestodene intravaginal ring of reservoir design, comprising a gestodene silicone elastomer core encased in a non-medicated silicone sheath, separately manufactured by reaction injection moulding at 80 degrees C and heating vulcanization at 130 degrees C is reported. The test investigated the factors affecting drug release through a single variable method, taking the drug release rates of 21 days as standards. When changing the thickness of the controlling sheath outside, the ratio of the first day of drug release and mean daily release (MDR), named the relatively burst effect, is closing to 1 with the thickness of controlling sheath increasing, while the 1.25 mm sheath corresponding to 1.04 controlled the burst release effectively; a positive correlation (r = 0.992 2) existed between the average drug release (Q/t) and drug loading (A) within a certain range. The C6-165 controlling sheath with high solubility of GEST is easier to achieve controlled release of the drug; GEST crystalline power is more effective to implement controlled release of drugs among difficent states of the drug. A 1/4 fractional segment core gives a relatively burst effect of 1.76, while the 1/1 and 1/2 are 1.93 and 1.87 separately, at the same drug loading, concluding that use of a fractional segment core would allow development of a suitable GEST reservoir IVR. In summary, GEST reservoir-type IVR could be adjusted by the thickness of controlling sheath, the loading of drug, the material properties of controlling sheath, the dispersion state of drug, the additive composition and structure of intravaginal ring, to control the drug release behavior and achieve the desired drug release rate.

  12. Monthly reservoir inflow forecasting using a new hybrid SARIMA genetic programming approach

    Science.gov (United States)

    Moeeni, Hamid; Bonakdari, Hossein; Ebtehaj, Isa

    2017-03-01

    Forecasting reservoir inflow is one of the most important components of water resources and hydroelectric systems operation management. Seasonal autoregressive integrated moving average (SARIMA) models have been frequently used for predicting river flow. SARIMA models are linear and do not consider the random component of statistical data. To overcome this shortcoming, monthly inflow is predicted in this study based on a combination of seasonal autoregressive integrated moving average (SARIMA) and gene expression programming (GEP) models, which is a new hybrid method (SARIMA-GEP). To this end, a four-step process is employed. First, the monthly inflow datasets are pre-processed. Second, the datasets are modelled linearly with SARIMA and in the third stage, the non-linearity of residual series caused by linear modelling is evaluated. After confirming the non-linearity, the residuals are modelled in the fourth step using a gene expression programming (GEP) method. The proposed hybrid model is employed to predict the monthly inflow to the Jamishan Dam in west Iran. Thirty years' worth of site measurements of monthly reservoir dam inflow with extreme seasonal variations are used. The results of this hybrid model (SARIMA-GEP) are compared with SARIMA, GEP, artificial neural network (ANN) and SARIMA-ANN models. The results indicate that the SARIMA-GEP model ( R 2=78.8, VAF =78.8, RMSE =0.89, MAPE =43.4, CRM =0.053) outperforms SARIMA and GEP and SARIMA-ANN ( R 2=68.3, VAF =66.4, RMSE =1.12, MAPE =56.6, CRM =0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid models indicates the superiority of SARIMA-GEP over the SARIMA-ANN model.

  13. Effects of the uncertainty of energy price and water availability forecasts on the operation of Alpine hydropower reservoir systems

    Science.gov (United States)

    Anghileri, D.; Castelletti, A.; Burlando, P.

    2016-12-01

    European energy markets have experienced dramatic changes in the last years because of the massive introduction of Variable Renewable Sources (VRSs), such as wind and solar power sources, in the generation portfolios in many countries. VRSs i) are intermittent, i.e., their production is highly variable and only partially predictable, ii) are characterized by no correlation between production and demand, iii) have negligible costs of production, and iv) have been largely subsidized. These features result in lower energy prices, but, at the same time, in increased price volatility, and in network stability issues, which pose a threat to traditional power sources because of smaller incomes and higher maintenance costs associated to a more flexible operation of power systems. Storage hydropower systems play an important role in compensating production peaks, both in term of excess and shortage of energy. Traditionally, most of the research effort in hydropower reservoir operation has focused on modeling and forecasting reservoir inflow as well as designing reservoir operation accordingly. Nowadays, price variability may be the largest source of uncertainty in the context of hydropower systems, especially when considering medium-to-large reservoirs, whose storage can easily buffer small inflow fluctuations. In this work, we compare the effects of uncertain inflow and energy price forecasts on hydropower production and profitability. By adding noise to historic inflow and price trajectories, we build a set of synthetic forecasts corresponding to different levels of predictability and assess their impact on reservoir operating policies and performances. The study is conducted on different hydropower systems, including storage systems and pumped-storage systems, with different characteristics, e.g., different inflow-capacity ratios. The analysis focuses on Alpine hydropower systems where the hydrological regime ranges from purely ice and snow-melt dominated to mixed snow

  14. Accuracy enhancement for forecasting water levels of reservoirs and river streams using a multiple-input-pattern fuzzification approach.

    Science.gov (United States)

    Valizadeh, Nariman; El-Shafie, Ahmed; Mirzaei, Majid; Galavi, Hadi; Mukhlisin, Muhammad; Jaafar, Othman

    2014-01-01

    Water level forecasting is an essential topic in water management affecting reservoir operations and decision making. Recently, modern methods utilizing artificial intelligence, fuzzy logic, and combinations of these techniques have been used in hydrological applications because of their considerable ability to map an input-output pattern without requiring prior knowledge of the criteria influencing the forecasting procedure. The artificial neurofuzzy interface system (ANFIS) is one of the most accurate models used in water resource management. Because the membership functions (MFs) possess the characteristics of smoothness and mathematical components, each set of input data is able to yield the best result using a certain type of MF in the ANFIS models. The objective of this study is to define the different ANFIS model by applying different types of MFs for each type of input to forecast the water level in two case studies, the Klang Gates Dam and Rantau Panjang station on the Johor river in Malaysia, to compare the traditional ANFIS model with the new introduced one in two different situations, reservoir and stream, showing the new approach outweigh rather than the traditional one in both case studies. This objective is accomplished by evaluating the model fitness and performance in daily forecasting.

  15. Forecasting of future earthquakes in the northeast region of India considering energy released concept

    Science.gov (United States)

    Zarola, Amit; Sil, Arjun

    2018-04-01

    This study presents the forecasting of time and magnitude size of the next earthquake in the northeast India, using four probability distribution models (Gamma, Lognormal, Weibull and Log-logistic) considering updated earthquake catalog of magnitude Mw ≥ 6.0 that occurred from year 1737-2015 in the study area. On the basis of past seismicity of the region, two types of conditional probabilities have been estimated using their best fit model and respective model parameters. The first conditional probability is the probability of seismic energy (e × 1020 ergs), which is expected to release in the future earthquake, exceeding a certain level of seismic energy (E × 1020 ergs). And the second conditional probability is the probability of seismic energy (a × 1020 ergs/year), which is expected to release per year, exceeding a certain level of seismic energy per year (A × 1020 ergs/year). The logarithm likelihood functions (ln L) were also estimated for all four probability distribution models. A higher value of ln L suggests a better model and a lower value shows a worse model. The time of the future earthquake is forecasted by dividing the total seismic energy expected to release in the future earthquake with the total seismic energy expected to release per year. The epicentre of recently occurred 4 January 2016 Manipur earthquake (M 6.7), 13 April 2016 Myanmar earthquake (M 6.9) and the 24 August 2016 Myanmar earthquake (M 6.8) are located in zone Z.12, zone Z.16 and zone Z.15, respectively and that are the identified seismic source zones in the study area which show that the proposed techniques and models yield good forecasting accuracy.

  16. Using a Bayesian Probabilistic Forecasting Model to Analyze the Uncertainty in Real-Time Dynamic Control of the Flood Limiting Water Level for Reservoir Operation

    DEFF Research Database (Denmark)

    Liu, Dedi; Li, Xiang; Guo, Shenglian

    2015-01-01

    Dynamic control of the flood limiting water level (FLWL) is a valuable and effective way to maximize the benefits from reservoir operation without exceeding the design risk. In order to analyze the impacts of input uncertainty, a Bayesian forecasting system (BFS) is adopted. Applying quantile water...... inflow values and their uncertainties obtained from the BFS, the reservoir operation results from different schemes can be analyzed in terms of benefits, dam safety, and downstream impacts during the flood season. When the reservoir FLWL dynamic control operation is implemented, there are two fundamental......, also deterministic water inflow was tested. The proposed model in the paper emphasizes the importance of analyzing the uncertainties of the water inflow forecasting system for real-time dynamic control of the FLWL for reservoir operation. For the case study, the selected quantile inflow from...

  17. Forecasting the remaining reservoir capacity in the Laurentian Great Lakes watershed

    Science.gov (United States)

    Alighalehbabakhani, Fatemeh; Miller, Carol J.; Baskaran, Mark; Selegean, James P.; Barkach, John H.; Dahl, Travis; Abkenar, Seyed Mohsen Sadatiyan

    2017-12-01

    Sediment accumulation behind a dam is a significant factor in reservoir operation and watershed management. There are many dams located within the Laurentian Great Lakes watershed whose operations have been adversely affected by excessive reservoir sedimentation. Reservoir sedimentation effects include reduction of flood control capability and limitations to both water supply withdrawals and power generation due to reduced reservoir storage. In this research, the sediment accumulation rates of twelve reservoirs within the Great Lakes watershed were evaluated using the Soil and Water Assessment Tool (SWAT). The estimated sediment accumulation rates by SWAT were compared to estimates relying on radionuclide dating of sediment cores and bathymetric survey methods. Based on the sediment accumulation rate, the remaining reservoir capacity for each study site was estimated. Evaluation of the anthropogenic impacts including land use change and dam construction on the sediment yield were assessed in this research. The regression analysis was done on the current and pre-European settlement sediment yield for the modeled watersheds to predict the current and natural sediment yield in un-modeled watersheds. These eleven watersheds are in the state of Indiana, Michigan, Ohio, New York, and Wisconsin.

  18. Coalbed Methane Production System Simulation and Deliverability Forecasting: Coupled Surface Network/Wellbore/Reservoir Calculation

    Directory of Open Access Journals (Sweden)

    Jun Zhou

    2017-01-01

    Full Text Available As an unconventional energy, coalbed methane (CBM mainly exists in coal bed with adsorption, whose productivity is different from conventional gas reservoir. This paper explains the wellbore pressure drop, surface pipeline network simulation, and reservoir calculation model of CBM. A coupled surface/wellbore/reservoir calculation architecture was presented, to coordinate the gas production in each calculation period until the balance of surface/wellbore/reservoir. This coupled calculation method was applied to a CBM field for predicting production. The daily gas production increased year by year at the first time and then decreased gradually after several years, while the daily water production was reduced all the time with the successive decline of the formation pressure. The production of gas and water in each well is almost the same when the structure is a star. When system structure is a dendritic surface system, the daily gas production ranked highest at the well which is the nearest to the surface system collection point and lowest at the well which is the farthest to the surface system collection point. This coupled calculation method could be used to predict the water production, gas production, and formation pressure of a CBM field during a period of time.

  19. Operational reservoir inflow forecasting with radar altimetry: The Zambezi case study

    DEFF Research Database (Denmark)

    Michailovsky, Claire Irene B.; Bauer-Gottwein, Peter

    2014-01-01

    cannot be measured from space, radar altimetry can track surface water level variations at crossing locations between the satellite ground track and the river system called virtual stations (VS). Use of radar altimetry versus traditional monitoring in operational settings is complicated by the low......River basin management can greatly benefit from short-term river discharge predictions. In order to improve model produced discharge forecasts, data assimilation allows for the integration of current observations of the hydrological system to produce improved forecasts and reduce prediction...... uncertainty. Data assimilation is widely used in operational applications to update hydrological models with in situ discharge or level measurements. In areas where timely access to in situ data is not possible, remote sensing data products can be used in assimilation schemes. While river discharge itself...

  20. Use of bias correction techniques to improve seasonal forecasts for reservoirs - A case-study in northwestern Mediterranean.

    Science.gov (United States)

    Marcos, Raül; Llasat, Ma Carmen; Quintana-Seguí, Pere; Turco, Marco

    2018-01-01

    In this paper, we have compared different bias correction methodologies to assess whether they could be advantageous for improving the performance of a seasonal prediction model for volume anomalies in the Boadella reservoir (northwestern Mediterranean). The bias correction adjustments have been applied on precipitation and temperature from the European Centre for Middle-range Weather Forecasting System 4 (S4). We have used three bias correction strategies: two linear (mean bias correction, BC, and linear regression, LR) and one non-linear (Model Output Statistics analogs, MOS-analog). The results have been compared with climatology and persistence. The volume-anomaly model is a previously computed Multiple Linear Regression that ingests precipitation, temperature and in-flow anomaly data to simulate monthly volume anomalies. The potential utility for end-users has been assessed using economic value curve areas. We have studied the S4 hindcast period 1981-2010 for each month of the year and up to seven months ahead considering an ensemble of 15 members. We have shown that the MOS-analog and LR bias corrections can improve the original S4. The application to volume anomalies points towards the possibility to introduce bias correction methods as a tool to improve water resource seasonal forecasts in an end-user context of climate services. Particularly, the MOS-analog approach gives generally better results than the other approaches in late autumn and early winter. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. On the Techa’s reservoirs cascade influence on the long-term forecast of the Techa river radioactive contamination

    Directory of Open Access Journals (Sweden)

    S. S. Utkin

    2016-01-01

    Full Text Available In 1949–1956 years, the Techa river was exposed to the intense radioactive contamination, which consequences are not overcome up to now. Currently, the Techa Cascade of Water Reservoirs is the only source of contamination of this river that could be managed. In February 2016 the Chief Executive Officer of the State Corporation “ROSATOM” approved the «Strategic master-plan on the solution of the problems of the Techa Reservoir Cascade» providing a novel look at an issue of remediation of the Techa river. The aim of the article is the implementation of the modern radiation protection system to the existing or potential exposure situations of public residing near the Techa river and an analysis of possible features, events, and processes considered in the longterm forecasts performed in the field of public radiation safety. Although the current radiation state of the Techa River is relatively stable, the task of refining the traditional phenomenological retrospective analysis covering the assessment of the past and current radiation exposure and environmental impacts is considered quite relevant. The Calculation- monitoring complex “TCR-Prognoz” was developed in the framework of the “Strategic Master Plan”. This complex enables to evaluate multivariate scenario calculations resulting in long-term forecasts of radioactive contamination levels in the Techa River and its floodplain, depending on various sets of environmental conditions and anthropogenic factors. Complex radiation surveys to define the detailed character and the time frames of economic activities permitted under the existing radiation safety requirements in the floodplain of the Techa river are recommended to be started after 2020. By this time, the first steady effects associated with the “Strategic Master Plan” implementation will become evident, including those resulting from the efforts aimed at simultaneous minimization of radionuclide

  2. Trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma, 1951–2011

    Science.gov (United States)

    Wagner, Daniel M.; Krieger, Joshua D.; Merriman, Katherine R.

    2014-01-01

    The U.S. Geological Survey (USGS) and the U.S. Army Corps of Engineers (USACE) conducted a statistical analysis of trends in precipitation, streamflow, reservoir pool elevations, and reservoir releases in Arkansas and selected sites in Louisiana, Missouri, and Oklahoma for the period 1951–2011. The Mann-Kendall test was used to test for trends in annual and seasonal precipitation, annual and seasonal streamflows of 42 continuous-record USGS streamflow-gaging stations, annual pool elevations and releases from 16 USACE reservoirs, and annual releases from 11 dams on the Arkansas River. A statistically significant (p≤0.10) upward trend was observed in annual precipitation for the State, with a Sen slope of approximately 0.10 inch per year. Autumn and winter were the only seasons that had statistically significant trends in precipitation. Five of six physiographic sections and six of seven 4-digit hydrologic unit code (HUC) regions in Arkansas had statistically significant upward trends in autumn precipitation, with Sen slopes of approximately 0.06 to 0.10 inch per year. Sixteen sites had statistically significant upward trends in the annual mean daily streamflow and were located on streams that drained regions with statistically significant upward trends in annual precipitation. Expected annual rates of change corresponding to statistically significant trends in annual mean daily streamflows, which ranged from 0.32 to 0.88 percent, were greater than those corresponding to regions with statistically significant upward trends in annual precipitation, which ranged from 0.19 to 0.28 percent, suggesting that the observed trends in regional annual precipitation do not fully account for the observed trends in annual mean daily streamflows. Trends in annual maximum daily streamflows were similar to trends in the annual mean daily streamflows but were only statistically significant at seven sites. There were more statistically significant trends (28 of 42 sites) in the

  3. Forecasting the consequences of accidental releases of radionuclides in the atmosphere from ensemble dispersion modelling

    International Nuclear Information System (INIS)

    Galmarini, S.; Bianconi, R.; Bellasio, R.; Graziani, G.

    2001-01-01

    The RTMOD system is presented as a tool for the intercomparison of long-range dispersion models as well as a system for support of decision making. RTMOD is an internet-based procedure that collects the results of more than 20 models used around the world to predict the transport and deposition of radioactive releases in the atmosphere. It allows the real-time acquisition of model results and their intercomparison. Taking advantage of the availability of several model results, the system can also be used as a tool to support decision making in case of emergency. The new concept of ensemble dispersion modelling is introduced which is the basis for the decision-making application of RTMOD. New statistical parameters are presented that allow gathering the results of several models to produce a single dispersion forecast. The devised parameters are presented and tested on the results of RTMOD exercises

  4. Fundamental Study of Disposition and Release of Methane in a Shale Gas Reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yifeng [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Xiong, Yongliang [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Repository Performance; Criscenti, Louise J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Ho, Tuan Ahn [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Weck, Philippe F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Storage and Transportation Technology; Ilgen, Anastasia G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geochemistry; Matteo, Edward [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Kruichak, Jessica N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Mills, Melissa M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Nuclear Waste Disposal Research and Analysis; Dewers, Thomas [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Geomechanics; Gordon, Margaret E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States). Dept. of Materials, Devices and Energy Technologies; Akkutlu, Yucel [Texas A & M Univ., College Station, TX (United States). Dept. of Petroleum Engineering

    2016-09-01

    simulations also indicate that a significant fraction (3 - 35%) of methane deposited in kerogen can potentially become trapped in isolated nanopores and thus not recoverable. We have successfully established experimental capabilities for measuring gas sorption and desorption on shale and model materials under a wide range of physical and chemical conditions. Both low and high pressure measurements show significant sorption of CH4 and CO2 onto clays, implying that methane adsorbed on clay minerals could contribute a significant portion of gas-in-place in an unconventional reservoir. We have also studied the potential impact of the interaction of shale with hydrofracking fluid on gas sorption. We have found that the CH4-CO2 sorption capacity for the reacted sample is systematically lower (by a factor of ~2) than that for the unreacted (raw) sample. This difference in sorption capacity may result from a mineralogical or surface chemistry change of the shale sample induced by fluid-rock interaction. Our results shed a new light on mechanistic understanding gas release and production decline in unconventional reservoirs.

  5. Evaluation of Management of Water Release for Painted Rocks Reservoir, Bitterroot River, Montana, 1984 Annual Report.

    Energy Technology Data Exchange (ETDEWEB)

    Lere, Mark E. (Montana Department of Fish, Wildlife and Parks, Missoula, MT)

    1984-11-01

    Baseline fisheries and habitat data were gathered during 1983 and 1984 to evaluate the effectiveness of supplemental water releases from Painted Rocks Reservoir in improving the fisheries resource in the Bitterroot River. Discharge relationships among main stem gaging stations varied annually and seasonally. Flow relationships in the river were dependent upon rainfall events and the timing and duration of the irrigation season. Daily discharge monitored during the summers of 1983 and 1984 was greater than median values derived at the U.S.G.S. station near Darby. Supplemental water released from Painted Rocks Reservoir totaled 14,476 acre feet in 1983 and 13,958 acre feet in 1984. Approximately 63% of a 5.66 m{sup 3}/sec test release of supplemental water conducted during April, 1984 was lost to irrigation withdrawals and natural phenomena before passing Bell Crossing. A similar loss occurred during a 5.66 m{sup 3}/sec test release conducted in August, 1984. Daily maximum temperature monitored during 1984 in the Bitterroot River averaged 11.0, 12.5, 13.9 and 13.6 C at the Darby, Hamilton, Bell and McClay stations, respectively. Chemical parameters measured in the Bitterroot River were favorable to aquatic life. Population estimates conducted in the Fall, 1983 indicated densities of I+ and older rainbow trout (Salmo gairdneri) were significantly greater in a control section than in a dewatered section (p < 0.20). Numbers of I+ and older brown trout (Salmo trutta) were not significantly different between the control and dewatered sections (p > 0.20). Population and biomass estimates for trout in the control section were 631/km and 154.4 kg/km. In the dewatered section, population and biomass estimates for trout were 253/km and 122.8 kg/km. The growth increments of back-calculated length for rainbow trout averaged 75.6 mm in the control section and 66.9mm in the dewatered section. The growth increments of back-calculated length for brown trout averaged 79.5 mm in the

  6. Reservoir inflow forecasting with a modified coactive neuro-fuzzy inference system: a case study for a semi-arid region

    Science.gov (United States)

    Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Mohd, Nuruol Syuhadaa; Deo, Ravinesh C.; El-Shafie, Ahmed

    2017-10-01

    Existing forecast models applied for reservoir inflow forecasting encounter several drawbacks, due to the difficulty of the underlying mathematical procedures being to cope with and to mimic the naturalization and stochasticity of the inflow data patterns. In this study, appropriate adjustments to the conventional coactive neuro-fuzzy inference system (CANFIS) method are proposed to improve the mathematical procedure, thus enabling a better detection of the high nonlinearity patterns found in the reservoir inflow training data. This modification includes the updating of the back propagation algorithm, leading to a consequent update of the membership rules and the induction of the centre-weighted set rather than the global weighted set used in feature extraction. The modification also aids in constructing an integrated model that is able to not only detect the nonlinearity in the training data but also the wide range of features within the training data records used to simulate the forecasting model. To demonstrate the model's efficacy, the proposed CANFIS method has been applied to forecast monthly inflow data at Aswan High Dam (AHD), located in southern Egypt. Comparative analyses of the forecasting skill of the modified CANFIS and the conventional ANFIS model are carried out with statistical score indicators to assess the reliability of the developed method. The statistical metrics support the better performance of the developed CANFIS model, which significantly outperforms the ANFIS model to attain a low relative error value (23%), mean absolute error (1.4 BCM month-1), root mean square error (1.14 BCM month-1), and a relative large coefficient of determination (0.94). The present study ascertains the better utility of the modified CANFIS model in respect to the traditional ANFIS model applied in reservoir inflow forecasting for a semi-arid region.

  7. Modeling the wind-fields of accidental releases with an operational regional forecast model

    International Nuclear Information System (INIS)

    Albritton, J.R.; Lee, R.L.; Sugiyama, G.

    1995-01-01

    The Atmospheric Release Advisory Capability (ARAC) is an operational emergency preparedness and response organization supported primarily by the Departments of Energy and Defense. ARAC can provide real-time assessments of atmospheric releases of radioactive materials at any location in the world. ARAC uses robust three-dimensional atmospheric transport and dispersion models, extensive geophysical and dose-factor databases, meteorological data-acquisition systems, and an experienced staff. Although it was originally conceived and developed as an emergency response and assessment service for nuclear accidents, the ARAC system has been adapted to also simulate non-radiological hazardous releases. For example, in 1991 ARAC responded to three major events: the oil fires in Kuwait, the eruption of Mt. Pinatubo in the Philippines, and the herbicide spill into the upper Sacramento River in California. ARAC's operational simulation system, includes two three-dimensional finite-difference models: a diagnostic wind-field scheme, and a Lagrangian particle-in-cell transport and dispersion scheme. The meteorological component of ARAC's real-time response system employs models using real-time data from all available stations near the accident site to generate a wind-field for input to the transport and dispersion model. Here we report on simulation studies of past and potential release sites to show that even in the absence of local meteorological observational data, readily available gridded analysis and forecast data and a prognostic model, the Navy Operational Regional Atmospheric Prediction System, applied at an appropriate grid resolution can successfully simulate complex local flows

  8. Evaluating Potential for Large Releases from CO2 Storage Reservoirs: Analogs, Scenarios, and Modeling Needs

    International Nuclear Information System (INIS)

    Birkholzer, Jens; Pruess, Karsten; Lewicki, Jennifer; Tsang, Chin-Fu; Karimjee, Anhar

    2005-01-01

    While the purpose of geologic storage of CO 2 in deep saline formations is to trap greenhouse gases underground, the potential exists for CO 2 to escape from the target reservoir, migrate upward along permeable pathways, and discharge at the land surface. Such discharge is not necessarily a serious concern, as CO 2 is a naturally abundant and relatively benign gas in low concentrations. However, there is a potential risk to health, safety and environment (HSE) in the event that large localized fluxes of CO 2 were to occur at the land surface, especially where CO 2 could accumulate. In this paper, we develop possible scenarios for large CO 2 fluxes based on the analysis of natural analogues, where large releases of gas have been observed. We are particularly interested in scenarios which could generate sudden, possibly self-enhancing, or even eruptive release events. The probability for such events may be low, but the circumstances under which they might occur and potential consequences need to be evaluated in order to design appropriate site selection and risk management strategies. Numerical modeling of hypothetical test cases is needed to determine critical conditions for such events, to evaluate whether such conditions may be possible at designated storage sites, and, if applicable, to evaluate the potential HSE impacts of such events and design appropriate mitigation strategies

  9. Storage and Release of Spermatozoa from the Pre-Uterine Tube Reservoir

    Science.gov (United States)

    Freeman, Sarah L.; England, Gary C.W.

    2013-01-01

    In mammals, after coitus a small number of spermatozoa enter the uterine tube and following attachment to uterine tube epithelium are arrested in a non-capacitated state until peri-ovulatory signalling induces their detachment. Whilst awaiting release low numbers of spermatozoa continually detach from the epithelium and the uterine tube reservoir risks depletion. There is evidence of attachment of spermatozoa to uterine epithelium in several species which might form a potential pre-uterine tube reservoir. In this study we demonstrate that: (1) dog spermatozoa attach to uterine epithelium and maintain flagellar activity, (2) in non-capacitating conditions spermatozoa progressively detach with a variety of motility characteristics, (3) attachment is not influenced by epithelial changes occurring around ovulation, (4) attachment to uterine epithelium slows capacitation, (5) capacitated spermatozoa have reduced ability to attach to uterine epithelium, (6) under capacitating conditions increased numbers of spermatozoa detach and exhibit transitional and hyperactive motility which differ to those seen in non-capacitating conditions, (7) detachment of spermatozoa and motility changes can be induced by post-ovulation but not pre-ovulation uterine tube flush fluid and by components of follicular fluid and solubilised zona pellucida, (8) prolonged culture does not change the nature of the progressive detachment seen in non-capacitating conditions nor the potential for increased detachment in capacitating conditions. We postulate that in some species binding of spermatozoa to uterine epithelium is an important component of the transport of spermatozoa. Before ovulation low numbers of spermatozoa continually detach, including those which are non-capacitated with fast forward progressive motility allowing the re-population of the uterine tube, whilst around the time of ovulation, signalling from as-yet unknown factors associated with follicular fluid, oocytes and uterine tube

  10. Airborne Snow Observatory: measuring basin-wide seasonal snowpack with LiDAR and an imaging spectrometer to improve runoff forecasting and reservoir operation (Invited)

    Science.gov (United States)

    McGurk, B. J.; Painter, T. H.

    2013-12-01

    The Airborne Snow Observatory (ASO) NASA-JPL demonstration mission collected detailed snow information for portions of the Tuolumne Basin in California and the Uncompahgre Basin in Colorado in spring of 2013. The ASO uses an imaging spectrometer and LiDAR sensors mounted in an aircraft to collect snow depth and extent data, and snow albedo. By combining ground and modeled density fields, the ~weekly flights over the Tuolumne produced both basin-wide and detailed sub-basin snow water equivalent (SWE) estimates that were used in a hydrologic simulation model to improve the accuracy and timing of runoff forecasting tools used to manage Hetch Hetchy Reservoir, the source of 85% of the water supply for 2.5 million people on the San Francisco Peninsula. The USGS PRMS simulation model was calibrated to the 459 square mile basin and was updated with both weather forecast data and distributed snow information from ASO flights to inform the reservoir operators of predicted inflow volumes and timing. Information produced by the ASO data collection was used to update distributed SWE and albedo state variables in the PRMS model and improved inflow forecasts for Hetch Hetchy. Data from operational ASO programs is expected to improve the ability of reservoir operators to more efficiently allocate the last half of the recession limb of snowmelt inflow and be more assured of meeting operational mandates. This presentation will provide results from the project after its first year.

  11. Evaluation of Management of Water Releases for Painted Rocks Reservoir, Bitterroot River, Montana, 1983-1986, Final Report.

    Energy Technology Data Exchange (ETDEWEB)

    Spoon, Ronald L. (Montana Department of Fish, Wildlife and Parks, Missoula, MT)

    1987-06-01

    This study was initiated in July, 1983 to develop a water management plan for the release of water purchased from Painted Rocks Reservoir. Releases were designed to provide optimum benefits to the Bitterroot River fishery. Fisheries, habitat, and stream flow information was gathered to evaluate the effectiveness of these supplemental releases in improving trout populations in the Bitterroot River. The study was part of the Northwest Power Planning Council's Fish and Wildlife Program and was funded by the Bonneville Power Administration. This report presents data collected from 1983 through 1986.

  12. Nambe Pueblo Water Budget and Forecasting model.

    Energy Technology Data Exchange (ETDEWEB)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  13. [Sediment-water flux and processes of nutrients and gaseous nitrogen release in a China River Reservoir].

    Science.gov (United States)

    Chen, Zhu-hong; Chen, Neng-wang; Wu, Yin-qi; Mo, Qiong-li; Zhou, Xing-peng; Lu, Ting; Tian, Yun

    2014-09-01

    The key processes and fluxes of nutrients (N and P) and gaseous N (N2 and N2O) across the sediment-water interface in a river reservoir (Xipi) of the Jiulong River watershed in southeast China were studied. Intact core sediment incubation of nutrients exchange, in-situ observation and lab incubation of excess dissolved N2 and N2O (products of nitrification, denitrification and Anammox), and determination of physiochemical and microbe parameters were carried out in 2013 for three representative sites along the lacustrine zone of the reservoir. Results showed that ammonium and phosphate were generally released from sediment to overlying water [with averaged fluxes of N (479.8 ± 675.4) mg. (m2. d)-1 and P (4. 56 ± 0.54) mg. (m2 d) -1] , while nitrate and nitrite diffused into the sediment. Flood events in the wet season could introduce a large amount of particulate organic matter that would be trapped by the dam reservoir, resulting in the high release fluxes of ammonium and phosphate observed in the following low-flow season. No clear spatial variation of sediment nutrient release was found in the lacustrine zone of the reservoir. Gaseous N release was dominated by excess dissolved N2 (98% of total), and the N2 flux from sediment was (15.8 ± 12. 5) mg (m2. d) -1. There was a longitudinal and vertical variation of excess dissolved N2, reflecting the combined results of denitrification and Anammox occurring in anoxic sediment and fluvial transport. Nitrification mainly occurred in the lower lacustrine zone, and the enrichment of N2O was likely regulated by the ratio of ammonium to DIN in water.

  14. Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain).

    Science.gov (United States)

    Cánovas, Carlos Ruiz; Olias, Manuel; Vazquez-Suñé, Enric; Ayora, Carlos; Miguel Nieto, Jose

    2012-02-01

    The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12-16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2-4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. Copyright © 2011 Elsevier B.V. All rights reserved.

  15. Structure and Dynamics of Floods in the upper Delaware River Basin: An Integrated Seasonal Forecasting System for New York City Reservoirs

    Science.gov (United States)

    Najibi, N.; Devineni, N.

    2016-12-01

    The National Weather Service River Forecasting System (NWS-RFS) issues 3-month lead probabilistic forecasts of streamflow for many river basins in the contiguous United States from 12 river forecasting centers. The Ensemble Streamflow Prediction system from NWS-RFS uses conceptual hydrologic models to issue streamflow forecasts based on the current soil moisture, river, and reservoir conditions by assuming that past meteorological events will recur in the future with historical probabilities. Recent investigations focusing on the teleconnection between anomalous sea surface temperature conditions and regional/continental hydroclimatology show that interannual and interdecadal variability in exogenous climatic indices modulates the regional streamflow patterns. In this work, we present a comprehensive framework to quantify the structure and dynamics of floods for the upper Delaware River Basin based on the interaction between the exogenous climate and weather patterns and antecedent flow regimes. We focus on estimating the conditional distribution of flood volume, duration, peak and timing based on large-scale climatic teleconnections (seasonal sea level pressure and pre-season sea surface temperature) and macroscale hydrological factors (start of the season's flow, seasonal rainfall duration and intensity, pre-season snow depth and cover in watershed, and concurrent rain over snow (ROS) events). Statistical techniques such as the semi-parametric k-nearest neighbor resampling, multivariate Kalman filters, and hierarchical Bayesian methods are explored as a strategy to address both model and parameter uncertainties. Ultimately proactive decision models embedded into the operating rules based on the forecasted future conditions -instead of reactive decisions based on current observed conditions- can result in risk mitigation.

  16. Influence of releases from a fresh water reservoir on the hydrochemistry of the Tinto River (SW Spain)

    International Nuclear Information System (INIS)

    Cánovas, Carlos Ruiz; Olias, Manuel; Vazquez-Suñé, Enric; Ayora, Carlos; Nieto, Jose Miguel

    2012-01-01

    The Tinto River is an extreme case of pollution by acid mine drainage (AMD), with pH values below 3 and high sulphate, metal and metalloid concentrations along its main course. This study evaluates the impact of releases from a freshwater reservoir on the Tinto River, identifying the metal transport mechanisms. This information is needed to understand the water quality evolution in the long term, and involves the comprehension of interactions between AMD sources, freshwaters, particulate matter and sediments. This work proposes a methodology for quantifying the proportions in which the different sources are contributing. The method is based on the mass balance of solutes and accounts for the uncertainty of end-members. The impact of the releases from the Corumbel Reservoir on the hydrochemistry of the Tinto River was significant, accounting up to a 92% of river discharge. These releases provoked a sharp decrease in dissolved metal concentrations, especially for Fe (approximately 1000 fold) due to dilution and precipitation. Cadmium, Zn, Cu, Co, Ni and Al suffered a dilution to a 12–16 fold decrease while Ca, Sr, Na, Pb and Si were less affected (2–4 folds decrease). However, these releases also gave rise to an increase in particulate transport, mainly Fe, As, Cr, Ba, Pb and Ti, due to sediment remobilisation and Fe precipitation. Aluminium, Li, K, Si, Al, Ni and Sr, together with Cu were present in the particulate phase during the discharge peak. The proposed 2-component mixing model revealed the existence of non-conservative behaviour for Al, Ca, Li, Mn, Ni and Si as a consequence of the interactions between the acidic Tinto waters and the clay-rich reservoir sediments during the bottom outlet opening. These results were improved by a 3-component mixing model, introducing a new end-member to account the chemical dissolution of clay-rich sediments by acidic Tinto waters. - Highlights: ► We study the influence of freshwater releases on the acidic Tinto river

  17. Environmental release of dioxins from reservoir sources during beach nourishment programs.

    Science.gov (United States)

    Tondeur, Yves; Vining, Bryan; Mace, Kimberly; Mills, William; Hart, Jerry

    2012-07-01

    ,4,6,9-chlorination pattern across homolog groups. No other chlorinated aromatics were detected above background levels. The observations, along with the absence or an extremely low level of polychlorinated dibenzofurans, together with the mineralogical analysis, supports the conclusion that off-shore dredging activities are reaching reservoir sources containing dioxin-tainted, smectic/kaolinite clay minerals. Subsequent beach erosion provides additional environmental releases over time, as buried balls of clay from previous nourishment efforts become exposed. Copyright © 2012 Elsevier Ltd. All rights reserved.

  18. Preparation and Characterization of Kynurenic Acid Occluded in Sol-Gel Silica and SBA-15 Silica as Release Reservoirs

    Directory of Open Access Journals (Sweden)

    Tessy López

    2014-01-01

    Full Text Available Kynurenic acid (KYNA may have important therapeutic effects in neurological disorders; however, its use as a neuroprotective agent is restricted due to its very limited ability to cross the blood brain barrier (BBB. For this reason, we are looking for new alternatives for KYNA to reach the brain; one of them is using drug delivery systems. To obtain KYNA release reservoirs, KYNA molecules were hosted in two different silica materials. The different KYNA-silica materials were characterized by means of several physical techniques. The spectroscopic studies showed that KYNA molecules remained unchanged once hosted in silica materials. The surface area values of KYNA-silica samples were substantially lower than those for pure silica materials due to the addition of the drug. The electronic micrographs showed that the sol-gel KYNA-silica material consisted of aggregates of nanoparticles around 50 nm in size. On the other hand, the typical SBA-15 hexagonal arrangement was observed, even when hosting KYNA molecules. KYNA release profiles, carried out during approximately 300 hours, showed a first stage of fast drug release followed by a slow release phase. The experimental values fitted to the Peppas equation indicate that the release mechanism was controlled by Fickian diffusion.

  19. Cellular automata model for drug release from binary matrix and reservoir polymeric devices.

    Science.gov (United States)

    Johannes Laaksonen, Timo; Mikael Laaksonen, Hannu; Tapio Hirvonen, Jouni; Murtomäki, Lasse

    2009-04-01

    Kinetics of drug release from polymeric tablets, inserts and implants is an important and widely studied area. Here we present a new and widely applicable cellular automata model for diffusion and erosion processes occurring during drug release from polymeric drug release devices. The model divides a 2D representation of the release device into an array of cells. Each cell contains information about the material, drug, polymer or solvent that the domain contains. Cells are then allowed to rearrange according to statistical rules designed to match realistic drug release. Diffusion is modeled by a random walk of mobile cells and kinetics of chemical or physical processes by probabilities of conversion from one state to another. This is according to the basis of diffusion coefficients and kinetic rate constants, which are on fundamental level just probabilities for certain occurrences. The model is applied to three kinds of devices with different release mechanisms: erodable matrices, diffusion through channels or pores and membrane controlled release. The dissolution curves obtained are compared to analytical models from literature and the validity of the model is considered. The model is shown to be compatible with all three release devices, highlighting easy adaptability of the model to virtually any release system and geometry. Further extension and applications of the model are envisioned.

  20. Reservoir management

    International Nuclear Information System (INIS)

    Satter, A.; Varnon, J.E.; Hoang, M.T.

    1992-01-01

    A reservoir's life begins with exploration leading to discovery followed by delineation of the reservoir, development of the field, production by primary, secondary and tertiary means, and finally to abandonment. Sound reservoir management is the key to maximizing economic operation of the reservoir throughout its entire life. Technological advances and rapidly increasing computer power are providing tools to better manage reservoirs and are increasing the gap between good and neutral reservoir management. The modern reservoir management process involves goal setting, planning, implementing, monitoring, evaluating, and revising plans. Setting a reservoir management strategy requires knowledge of the reservoir, availability of technology, and knowledge of the business, political, and environmental climate. Formulating a comprehensive management plan involves depletion and development strategies, data acquisition and analyses, geological and numerical model studies, production and reserves forecasts, facilities requirements, economic optimization, and management approval. This paper provides management, engineers geologists, geophysicists, and field operations staff with a better understanding of the practical approach to reservoir management using a multidisciplinary, integrated team approach

  1. Forecast-Informed Reservoir Operations: Lessons Learned from a Multi-Agency Collaborative Research and Operations Effort to improve Flood Risk Management, Water Supply and Environmental Benefits

    Science.gov (United States)

    Talbot, C. A.; Ralph, M.; Jasperse, J.; Forbis, J.

    2017-12-01

    Lessons learned from the multi-agency Forecast-Informed Reservoir Operations (FIRO) effort demonstrate how research and observations can inform operations and policy decisions at Federal, State and Local water management agencies with the collaborative engagement and support of researchers, engineers, operators and stakeholders. The FIRO steering committee consists of scientists, engineers and operators from research and operational elements of the National Oceanographic and Atmospheric Administration and the US Army Corps of Engineers, researchers from the US Geological Survey and the US Bureau of Reclamation, the state climatologist from the California Department of Water Resources, the chief engineer from the Sonoma County Water Agency, and the director of the Scripps Institution of Oceanography's Center for Western Weather and Water Extremes at the University of California-San Diego. The FIRO framework also provides a means of testing and demonstrating the benefits of next-generation water cycle observations, understanding and models in water resources operations.

  2. Forecasting Three-Month Outcomes in a Laboratory School Comparison of Mixed Amphetamine Salts Extended Release (Adderall XR) and Atomoxetine (Strattera) in School-Aged Children with ADHD

    Science.gov (United States)

    Faraone, Stephen V.; Wigal, Sharon B.; Hodgkins, Paul

    2007-01-01

    Objective: Compare observed and forecasted efficacy of mixed amphetamine salts extended release (MAS-XR; Adderall) with atomoxetine (Strattera) in ADHD children. Method: The authors analyze data from a randomized, double-blind, multicenter, parallel-group, forced-dose-escalation laboratory school study of children ages 6 to 12 with ADHD combined…

  3. Bioturbation/bioirrigation effect on thallium released from reservoir sediment by different organism types.

    Science.gov (United States)

    He, Yi; Men, Bin; Yang, Xiaofang; Wang, Dongsheng

    2015-11-01

    Bioturbation can remobilize heavy metal in the sediments and may pose a risk for aquatic biota. The effects of bioturbation/bioirrigation by three different riverine organism types (Tubificid, Chironomid larvae, and Loach) on thallium release from contaminated sediment (10.0 ± 1.1 mg Tl/kg sediment, dry wt.) were evaluated in this study. The bioturbation by the epibenthos clearly caused an increased turbidity in the overlying water, and the effect was in the order of Loach > Chironomid larvae > Tubificid. A significant release of Tl into the water column via the resuspended sediment particles was observed, especially for Loach. During the first few days, the leaching of dissolved Tl from sediment into water was fast, and the dissolved Tl under bioturbation/bioirrigation was much higher than the control group. However, after 14 days, the bioturbation/bioirrigation process seemed to suppress the release of Tl from the sediment particles to water, especially for sediment with Loach. This may partly be due to the sorption or coprecipitation of Tl simultaneous with the formation of iron and manganese hydrous oxides with increased pH values as a consequence of phytoplankton growth. Linear regression analysis confirmed that both the total and particulate Tl concentrations had good correlations with particulate Fe and Mn concentrations as well as turbidity in the overlying water. Additionally, planktonic bacteria may oxidize the Tl(I) to Tl(III), resulting in a reduced solubility of Tl by which Tl(OH)3 becomes the predominant form of Tl. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Release of potential instability by mesoscale triggering - An objective model simulation. [in precipitation numerical weather forecasting

    Science.gov (United States)

    Matthews, D. A.

    1978-01-01

    The effects of mesoscale triggering on organized nonsevere convective cloud systems in the High Plains are considered. Two experiments were conducted to determine if a one-dimensional quasi-time dependent model could (1) detect soundings which were sensitive to mesoscale triggering, and (2) discriminate between cases which had mesoscale organized convection and those with no organized convection. The MESOCU model was used to analyze the available potential instability and thermodynamic potential for cloud growth. It is noted that lifting is a key factor in the release of available potential instability on the High Plains.

  5. Forecasting consequences of accidental release: how reliable are current assessment models

    International Nuclear Information System (INIS)

    Rohwer, P.S.; Hoffman, F.O.; Miller, C.W.

    1983-01-01

    This paper focuses on uncertainties in model output used to assess accidents. We begin by reviewing the historical development of assessment models and the associated interest in uncertainties as these evolutionary processes occurred in the United States. This is followed by a description of the sources of uncertainties in assessment calculations. Types of models appropriate for assessment of accidents are identified. A summary of results from our analysis of uncertainty is provided in results obtained with current methodology for assessing routine and accidental radionuclide releases to the environment. We conclude with discussion of preferred procedures and suggested future directions to improve the state-of-the-art of radiological assessments

  6. The Solar Reflectance Index as a Tool to Forecast the Heat Released to the Urban Environment: Potentiality and Assessment Issues

    Directory of Open Access Journals (Sweden)

    Alberto Muscio

    2018-02-01

    Full Text Available Overheating of buildings and urban areas is a more and more severe issue in view of global warming combined with increasing urbanization. The thermal behavior of urban surfaces in the hot seasons is the result of a complex balance of construction and environmental parameters such as insulation level, thermal mass, shielding, and solar reflective capability on one side, and ambient conditions on the other side. Regulations makers and the construction industry have favored the use of parameters that allow the forecasting of the interaction between different material properties without the need for complex analyses. Among these, the solar reflectance index (SRI takes into account solar reflectance and thermal emittance to predict the thermal behavior of a surface subjected to solar radiation through a physically rigorous mathematical procedure that considers assigned air and sky temperatures, peak solar irradiance, and wind velocity. The correlation of SRI with the heat released to the urban environment is analyzed in this paper, as well as the sensitivity of its calculation procedure to variation of the input parameters, as possibly induced by the measurement methods used or by the material ageing.

  7. Ensemble Streamflow Forecast Improvements in NYC's Operations Support Tool

    Science.gov (United States)

    Wang, L.; Weiss, W. J.; Porter, J.; Schaake, J. C.; Day, G. N.; Sheer, D. P.

    2013-12-01

    Like most other water supply utilities, New York City's Department of Environmental Protection (DEP) has operational challenges associated with drought and wet weather events. During drought conditions, DEP must maintain water supply reliability to 9 million customers as well as meet environmental release requirements downstream of its reservoirs. During and after wet weather events, DEP must maintain turbidity compliance in its unfiltered Catskill and Delaware reservoir systems and minimize spills to mitigate downstream flooding. Proactive reservoir management - such as release restrictions to prepare for a drought or preventative drawdown in advance of a large storm - can alleviate negative impacts associated with extreme events. It is important for water managers to understand the risks associated with proactive operations so unintended consequences such as endangering water supply reliability with excessive drawdown prior to a storm event are minimized. Probabilistic hydrologic forecasts are a critical tool in quantifying these risks and allow water managers to make more informed operational decisions. DEP has recently completed development of an Operations Support Tool (OST) that integrates ensemble streamflow forecasts, real-time observations, and a reservoir system operations model into a user-friendly graphical interface that allows its water managers to take robust and defensible proactive measures in the face of challenging system conditions. Since initial development of OST was first presented at the 2011 AGU Fall Meeting, significant improvements have been made to the forecast system. First, the monthly AR1 forecasts ('Hirsch method') were upgraded with a generalized linear model (GLM) utilizing historical daily correlations ('Extended Hirsch method' or 'eHirsch'). The development of eHirsch forecasts improved predictive skill over the Hirsch method in the first week to a month from the forecast date and produced more realistic hydrographs on the tail

  8. Well testing in gas hydrate reservoirs

    OpenAIRE

    Kome, Melvin Njumbe

    2015-01-01

    Reservoir testing and analysis are fundamental tools in understanding reservoir hydraulics and hence forecasting reservoir responses. The quality of the analysis is very dependent on the conceptual model used in investigating the responses under different flowing conditions. The use of reservoir testing in the characterization and derivation of reservoir parameters is widely established, especially in conventional oil and gas reservoirs. However, with depleting conventional reserves, the ...

  9. Hydrological ensemble predictions for reservoir inflow management

    Science.gov (United States)

    Zalachori, Ioanna; Ramos, Maria-Helena; Garçon, Rémy; Gailhard, Joel

    2013-04-01

    Hydrologic forecasting is a topic of special importance for a variety of users with different purposes. It concerns operational hydrologists interested in forecasting hazardous events (eg., floods and droughts) for early warning and prevention, as well as planners and managers searching to optimize the management of water resources systems at different space-time scales. The general aim of this study is to investigate the benefits of using hydrological ensemble predictions for reservoir inflow management. Ensemble weather forecasts are used as input to a hydrologic forecasting model and daily ensemble streamflow forecasts are generated up to a lead time of 7 days. Forecasts are then integrated into a heuristic decision model for reservoir management procedures. Performance is evaluated in terms of potential gain in energy production. The sensitivity of the results to various reservoir characteristics and future streamflow scenarios is assessed. A set of 11 catchments in France is used to illustrate the added value of ensemble streamflow forecasts for reservoir management.

  10. [Characteristics of dissolved organic carbon release under inundation from typical grass plants in the water-level fluctuation zone of the Three Gorges Reservoir area].

    Science.gov (United States)

    Tan, Qiu-Xia; Zhu, Boi; Hua, Ke-Ke

    2013-08-01

    The water-level fluctuation zone of the Three Gorges Reservoir (TGR) exposes in spring and summer, then, green plants especially herbaceous plants grow vigorously. In the late of September, water-level fluctuation zone of TGR goes to inundation. Meanwhile, annually accumulated biomass of plant will be submerged for decaying, resulting in organism decomposition and release a large amount of dissolved organic carbon (DOC). This may lead to negative impacts on water environment of TGR. The typical herbaceous plants from water-level fluctuation zone were collected and inundated in the laboratory for dynamic measurements of DOC concentration of overlying water. According to the determination, the DOC release rates and fluxes have been calculated. Results showed that the release process of DOC variation fitted in a parabolic curve. The peak DOC concentrations emerge averagely in the 15th day of inundation, indicating that DOC released quickly with organism decay of herbaceous plant. The release process of DOC could be described by the logarithm equation. There are significant differences between the concentration of DOC (the maximum DOC concentration is 486.88 mg x L(-1) +/- 35.97 mg x L(-1) for Centaurea picris, the minimum is 4.18 mg x L(-1) +/- 1.07 mg x L(-1) for Echinochloacrus galli) and the release amount of DOC (the maximum is 50.54 mg x g(-1) for Centaurea picris, the minimum is 6.51 mg x g(-1) for Polygonum hydropiper) due to different characteristics of plants, especially, the values of C/N of herbaceous plants. The cumulative DOC release quantities during the whole inundation period were significantly correlated with plants' C/N values in linear equations.

  11. Live-vaccinia virus encapsulation in pH-sensitive polymer increases safety of a reservoir-targeted Lyme disease vaccine by targeting gastrointestinal release.

    Science.gov (United States)

    Kern, Aurelie; Zhou, Chensheng W; Jia, Feng; Xu, Qiaobing; Hu, Linden T

    2016-08-31

    The incidence of Lyme disease has continued to rise despite attempts to control its spread. Vaccination of zoonotic reservoirs of human pathogens has been successfully used to decrease the incidence of rabies in raccoons and foxes. We have previously reported on the efficacy of a vaccinia virus vectored vaccine to reduce carriage of Borrelia burgdorferi in reservoir mice and ticks. One potential drawback to vaccinia virus vectored vaccines is the risk of accidental infection of humans. To reduce this risk, we developed a process to encapsulate vaccinia virus with a pH-sensitive polymer that inactivates the virus until it is ingested and dissolved by stomach acids. We demonstrate that the vaccine is inactive both in vitro and in vivo until it is released from the polymer. Once released from the polymer by contact with an acidic pH solution, the virus regains infectivity. Vaccination with coated vaccinia virus confers protection against B. burgdorferi infection and reduction in acquisition of the pathogen by naïve feeding ticks. Copyright © 2016. Published by Elsevier Ltd.

  12. Forecasting of reservoir pressures of oil and gas bearing complexes in northern part of West Siberia for safety oil and gas deposits exploration and development

    Science.gov (United States)

    Gorbunov, P. A.; Vorobyov, S. V.

    2017-10-01

    In the paper the features of reservoir pressures changes in the northern part of West Siberian oil-and gas province are described. This research is based on the results of hydrodynamic studies in prospecting and explorating wells in Yamal-Nenets Autonomous District. In the Cenomanian, Albian, Aptian and in the top of Neocomian deposits, according to the research, reservoir pressure is usually equal to hydrostatic pressure. At the bottom of the Neocomian and Jurassic deposits zones with abnormally high reservoir pressures (AHRP) are distinguished within Gydan and Yamal Peninsula and in the Nadym-Pur-Taz interfluve. Authors performed the unique zoning of the territory of the Yamal-Nenets Autonomous District according to the patterns of changes of reservoir pressures in the section of the sedimentary cover. The performed zoning and structural modeling allow authors to create a set of the initial reservoir pressures maps for the main oil and gas bearing complexes of the northern part of West Siberia. The results of the survey should improve the efficiency of exploration drilling by preventing complications and accidents during this operation in zones with abnormally high reservoir pressures. In addition, the results of the study can be used to estimate gas resources within prospective areas of Yamal-Nenets Autonomous District.

  13. Impact of Reservoir Operation to the Inflow Flood - a Case Study of Xinfengjiang Reservoir

    Science.gov (United States)

    Chen, L.

    2017-12-01

    Building of reservoir shall impact the runoff production and routing characteristics, and changes the flood formation. This impact, called as reservoir flood effect, could be divided into three parts, including routing effect, volume effect and peak flow effect, and must be evaluated in a whole by using hydrological model. After analyzing the reservoir flood formation, the Liuxihe Model for reservoir flood forecasting is proposed. The Xinfengjiang Reservoir is studied as a case. Results show that the routing effect makes peak flow appear 4 to 6 hours in advance, volume effect is bigger for large flood than small one, and when rainfall focus on the reservoir area, this effect also increases peak flow largely, peak flow effect makes peak flow increase 6.63% to 8.95%. Reservoir flood effect is obvious, which have significant impact to reservoir flood. If this effect is not considered in the flood forecasting model, the flood could not be forecasted accurately, particularly the peak flow. Liuxihe Model proposed for Xinfengjiang Reservoir flood forecasting has a good performance, and could be used for real-time flood forecasting of Xinfengjiang Reservoir.Key words: Reservoir flood effect, reservoir flood forecasting, physically based distributed hydrological model, Liuxihe Model, parameter optimization

  14. Modeling Reservoir-River Networks in Support of Optimizing Seasonal-Scale Reservoir Operations

    Science.gov (United States)

    Villa, D. L.; Lowry, T. S.; Bier, A.; Barco, J.; Sun, A.

    2011-12-01

    HydroSCOPE (Hydropower Seasonal Concurrent Optimization of Power and the Environment) is a seasonal time-scale tool for scenario analysis and optimization of reservoir-river networks. Developed in MATLAB, HydroSCOPE is an object-oriented model that simulates basin-scale dynamics with an objective of optimizing reservoir operations to maximize revenue from power generation, reliability in the water supply, environmental performance, and flood control. HydroSCOPE is part of a larger toolset that is being developed through a Department of Energy multi-laboratory project. This project's goal is to provide conventional hydropower decision makers with better information to execute their day-ahead and seasonal operations and planning activities by integrating water balance and operational dynamics across a wide range of spatial and temporal scales. This presentation details the modeling approach and functionality of HydroSCOPE. HydroSCOPE consists of a river-reservoir network model and an optimization routine. The river-reservoir network model simulates the heat and water balance of river-reservoir networks for time-scales up to one year. The optimization routine software, DAKOTA (Design Analysis Kit for Optimization and Terascale Applications - dakota.sandia.gov), is seamlessly linked to the network model and is used to optimize daily volumetric releases from the reservoirs to best meet a set of user-defined constraints, such as maximizing revenue while minimizing environmental violations. The network model uses 1-D approximations for both the reservoirs and river reaches and is able to account for surface and sediment heat exchange as well as ice dynamics for both models. The reservoir model also accounts for inflow, density, and withdrawal zone mixing, and diffusive heat exchange. Routing for the river reaches is accomplished using a modified Muskingum-Cunge approach that automatically calculates the internal timestep and sub-reach lengths to match the conditions of

  15. Reservoir optimisation using El Niño information. Case study of Daule Peripa (Ecuador)

    Science.gov (United States)

    Gelati, Emiliano; Madsen, Henrik; Rosbjerg, Dan

    2010-05-01

    The optimisation of water resources systems requires the ability to produce runoff scenarios that are consistent with available climatic information. We approach stochastic runoff modelling with a Markov-modulated autoregressive model with exogenous input, which belongs to the class of Markov-switching models. The model assumes runoff parameterisation to be conditioned on a hidden climatic state following a Markov chain, whose state transition probabilities depend on climatic information. This approach allows stochastic modeling of non-stationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We calibrate the model on the inflows of the Daule Peripa reservoir located in western Ecuador, where the occurrence of El Niño leads to anomalously heavy rainfall caused by positive sea surface temperature anomalies along the coast. El Niño - Southern Oscillation (ENSO) information is used to condition the runoff parameterisation. Inflow predictions are realistic, especially at the occurrence of El Niño events. The Daule Peripa reservoir serves a hydropower plant and a downstream water supply facility. Using historical ENSO records, synthetic monthly inflow scenarios are generated for the period 1950-2007. These scenarios are used as input to perform stochastic optimisation of the reservoir rule curves with a multi-objective Genetic Algorithm (MOGA). The optimised rule curves are assumed to be the reservoir base policy. ENSO standard indices are currently forecasted at monthly time scale with nine-month lead time. These forecasts are used to perform stochastic optimisation of reservoir releases at each monthly time step according to the following procedure: (i) nine-month inflow forecast scenarios are generated using ENSO forecasts; (ii) a MOGA is set up to optimise the upcoming nine monthly releases; (iii) the optimisation is carried out by simulating the releases on the

  16. Cesium accumulation by aquatic organisms at different trophic levels following an experimental release into a small reservoir

    Energy Technology Data Exchange (ETDEWEB)

    Pinder, J.E., E-mail: jepinder@uga.ed [Savannah River Ecology Laboratory, P. O. Drawer E, Aiken, SC 29802 (United States); Hinton, T.G., E-mail: thomas.hinton@irsn.f [Savannah River Ecology Laboratory, P. O. Drawer E, Aiken, SC 29802 (United States); Taylor, B.E., E-mail: TaylorB@dnr.sc.go [Savannah River Ecology Laboratory, P. O. Drawer E, Aiken, SC 29802 (United States); Whicker, F.W., E-mail: ward.whicker@colostate.ed [Department of Environmental and Radiological Health Sciences, Colorado, State University, Fort Collins, CO 80523-1618 (United States)

    2011-03-15

    The rates of accumulation and subsequent loss of stable cesium ({sup 133}Cs) by organisms at different trophic levels within plankton-based and periphyton-based food chains were measured following the addition of {sup 133}Cs into a small reservoir near Aiken, South Carolina, USA. An uptake parameter u (L kg{sup -1} d{sup -1} dry mass) and a loss rate parameter k (d{sup -1}) were estimated for each organism using time-series measurements of {sup 133}Cs concentrations in water and biota, and these parameters were used to estimate maximum concentrations, times to maximum concentrations, and concentration ratios (C{sub r}). The maximum {sup 133}Cs concentrations for plankton, periphyton, the insect larva Chaoborus punctipennis, which feeds on plankton, and the snail Helisoma trivolvis, which feeds on periphyton, occurred within the first 14 days following the addition, whereas the maximum concentrations for the fish species Lepomis macrochirus and Micropterus salmoides occurred after 170 days. The C{sub r} based on dry mass for plankton and C. punctipennis were 1220 L kg{sup -1} and 5570 L kg{sup -1}, respectively, and were less than the C{sub r} of 8630 L kg{sup -1} for periphyton and 47,700 L kg{sup -1} for H. trivolvis. Although the C{sub r} differed between plankton-based and periphyton-based food chains, they displayed similar levels of biomagnification. Biomagnification was also indicated for fish where the C{sub r} for the mostly nonpiscivorous L. macrochirus of 22,600 L kg{sup -1} was three times less than that for mostly piscivorous M. salmoides of 71,500 L kg{sup -1}. Although the C{sub r} for M. salmoides was greater than those for periphyton and H. trivolvis, the maximum {sup 133}Cs concentrations for periphyton and H. trivolvis were greater than that for M. salmoides. - Research highlights: {yields} A simple uptake and loss model described the Cs dynamics in all the various biota. {yields} Concentrations of Cs were greater in periphyton than in plankton

  17. Trade-off analysis of discharge-desiltation-turbidity and ANN analysis on sedimentation of a combined reservoir-reach system under multi-phase and multi-layer conjunctive releasing operation

    Science.gov (United States)

    Huang, Chien-Lin; Hsu, Nien-Sheng; Wei, Chih-Chiang; Yao, Chun-Hao

    2017-10-01

    Multi-objective reservoir operation considering the trade-off of discharge-desiltation-turbidity during typhoons and sediment concentration (SC) simulation modeling are the vital components for sustainable reservoir management. The purposes of this study were (1) to analyze the multi-layer release trade-offs between reservoir desiltation and intake turbidity of downstream purification plants and thus propose a superior conjunctive operation strategy and (2) to develop ANFIS-based (adaptive network-based fuzzy inference system) and RTRLNN-based (real-time recurrent learning neural networks) substitute SC simulation models. To this end, this study proposed a methodology to develop (1) a series of multi-phase and multi-layer sediment-flood conjunctive release modes and (2) a specialized SC numerical model for a combined reservoir-reach system. The conjunctive release modes involve (1) an optimization model where the decision variables are multi-phase reduction/scaling ratios and the timings to generate a superior total release hydrograph for flood control (Phase I: phase prior to flood arrival, Phase II/III: phase prior to/subsequent to peak flow) and (2) a combination method with physical limitations regarding separation of the singular hydrograph into multi-layer release hydrographs for sediment control. This study employed the featured signals obtained from statistical quartiles/sediment duration curve in mesh segmentation, and an iterative optimization model with a sediment unit response matrix and corresponding geophysical-based acceleration factors, for efficient parameter calibration. This research applied the developed methodology to the Shihmen Reservoir basin in Taiwan. The trade-off analytical results using Typhoons Sinlaku and Jangmi as case examples revealed that owing to gravity current and re-suspension effects, Phase I + II can de-silt safely without violating the intake's turbidity limitation before reservoir discharge reaches 2238 m3/s; however

  18. Timetable of an operational flood forecasting system

    Science.gov (United States)

    Liechti, Katharina; Jaun, Simon; Zappa, Massimiliano

    2010-05-01

    At present a new underground part of Zurich main station is under construction. For this purpose the runoff capacity of river Sihl, which is passing beneath the main station, is reduced by 40%. If a flood is to occur the construction site is evacuated and gates can be opened for full runoff capacity to prevent bigger damages. However, flooding the construction site, even if it is controlled, is coupled with costs and retardation. The evacuation of the construction site at Zurich main station takes about 2 to 4 hours and opening the gates takes another 1 to 2 hours each. In the upper part of the 336 km2 Sihl catchment the Sihl lake, a reservoir lake, is situated. It belongs and is used by the Swiss Railway Company for hydropower production. This lake can act as a retention basin for about 46% of the Sihl catchment. Lowering the lake level to gain retention capacity, and therewith safety, is coupled with direct loss for the Railway Company. To calculate the needed retention volume and the water to be released facing unfavourable weather conditions, forecasts with a minimum lead time of 2 to 3 days are needed. Since the catchment is rather small, this can only be realised by the use of meteorological forecast data. Thus the management of the construction site depends on accurate forecasts to base their decisions on. Therefore an operational hydrological ensemble prediction system (HEPS) was introduced in September 2008 by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). It delivers daily discharge forecasts with a time horizon of 5 days. The meteorological forecasts are provided by MeteoSwiss and stem from the operational limited-area COSMO-LEPS which downscales the ECMWF ensemble prediction system to a spatial resolution of 7 km. Additional meteorological data for model calibration and initialisation (air temperature, precipitation, water vapour pressure, global radiation, wind speed and sunshine duration) and radar data are also provided by

  19. Designing adaptive operating rules for a large multi-purpose reservoir

    Science.gov (United States)

    Geressu, Robel; Rougé, Charles; Harou, Julien

    2017-04-01

    Reservoirs whose live storage capacity is large compared with annual inflow have "memory", i.e., their storage levels contain information about past inflows and reservoir operations. Such "long-memory" reservoirs can be found in basins in dry regions such as the Nile River Basin in Africa, the Colorado River Basin in the US, or river basins in Western and Central Asia. There the effects of a dry year have the potential to impact reservoir levels and downstream releases for several subsequent years, prompting tensions in transboundary basins. Yet, current reservoir operation rules in those reservoirs do not reflect this by integrating past climate history and release decisions among the factors that influence operating decisions. This work proposes and demonstrates an adaptive reservoir operating rule that explicitly accounts for the recent history of release decisions, and not only current storage level and near-term inflow forecasts. This implies adding long-term (e.g., multiyear) objectives to the existing short-term (e.g., annual) ones. We apply these operating rules to the Grand Ethiopian Renaissance Dam, a large reservoir under construction on the Blue Nile River. Energy generation has to be balanced with the imperative of releasing enough water in low flow years (e.g., the minimum 1, 2 or 3 year cumulative flow) to avoid tensions with downstream countries, Sudan and Egypt. Maximizing the minimum multi-year releases could be of interest for the Nile problem to minimize the impact on performance of the large High Aswan Dam in Egypt. Objectives include maximizing the average and minimum annual energy generation and maximizing the minimum annual, two year and three year cumulative releases. The system model is tested using 30 stochastically generated streamflow series. One can then derive adaptive release rules depending on the value of one- and two-year total releases with respect to thresholds. Then, there are 3 sets of release rules for the reservoir depending

  20. Risk Based Reservoir Operations Using Ensemble Streamflow Predictions for Lake Mendocino in Mendocino County, California

    Science.gov (United States)

    Delaney, C.; Mendoza, J.; Whitin, B.; Hartman, R. K.

    2017-12-01

    Ensemble Forecast Operations (EFO) is a risk based approach of reservoir flood operations that incorporates ensemble streamflow predictions (ESPs) made by NOAA's California-Nevada River Forecast Center (CNRFC). With the EFO approach, each member of an ESP is individually modeled to forecast system conditions and calculate risk of reaching critical operational thresholds. Reservoir release decisions are computed which seek to manage forecasted risk to established risk tolerance levels. A water management model was developed for Lake Mendocino, a 111,000 acre-foot reservoir located near Ukiah, California, to evaluate the viability of the EFO alternative to improve water supply reliability but not increase downstream flood risk. Lake Mendocino is a dual use reservoir, which is owned and operated for flood control by the United States Army Corps of Engineers and is operated for water supply by the Sonoma County Water Agency. Due to recent changes in the operations of an upstream hydroelectric facility, this reservoir has suffered from water supply reliability issues since 2007. The EFO alternative was simulated using a 26-year (1985-2010) ESP hindcast generated by the CNRFC, which approximates flow forecasts for 61 ensemble members for a 15-day horizon. Model simulation results of the EFO alternative demonstrate a 36% increase in median end of water year (September 30) storage levels over existing operations. Additionally, model results show no increase in occurrence of flows above flood stage for points downstream of Lake Mendocino. This investigation demonstrates that the EFO alternative may be a viable approach for managing Lake Mendocino for multiple purposes (water supply, flood mitigation, ecosystems) and warrants further investigation through additional modeling and analysis.

  1. Incorporating teleconnection information into reservoir operating policies using Stochastic Dynamic Programming and a Hidden Markov Model

    Science.gov (United States)

    Turner, Sean; Galelli, Stefano; Wilcox, Karen

    2015-04-01

    Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating

  2. Developing an Intelligent Reservoir Flood Control Decision Support System through Integrating Artificial Neural Networks

    Science.gov (United States)

    Chang, L. C.; Kao, I. F.; Tsai, F. H.; Hsu, H. C.; Yang, S. N.; Shen, H. Y.; Chang, F. J.

    2015-12-01

    Typhoons and storms hit Taiwan several times every year and cause serious flood disasters. Because the mountainous terrain and steep landform rapidly accelerate the speed of flood flow, rivers cannot be a stable source of water supply. Reservoirs become one of the most important and effective floodwater storage facilities. However, real-time operation for reservoir flood control is a continuous and instant decision-making process based on rules, laws, meteorological nowcast, in addition to the immediate rainfall and hydrological data. The achievement of reservoir flood control can effectively mitigate flood disasters and store floodwaters for future uses. In this study, we construct an intelligent decision support system for reservoir flood control through integrating different types of neural networks and the above information to solve this problem. This intelligent reservoir flood control decision support system includes three parts: typhoon track classification, flood forecast and adaptive water release models. This study used the self-organizing map (SOM) for typhoon track clustering, nonlinear autoregressive with exogenous inputs (NARX) for multi-step-ahead reservoir inflow prediction, and adaptive neuro-fuzzy inference system (ANFIS) for reservoir flood control. Before typhoons landfall, we can estimate the entire flood hydrogragh of reservoir inflow by using SOM and make a pre-release strategy and real-time reservoir flood operating by using ANFIS. In the meanwhile, NARX can be constantly used real-time five-hour-ahead inflow prediction for providing the newest flood information. The system has been successfully implemented Typhoons Trami (2013), Fitow (2013) and Matmo (2014) in Shihmen Reservoir.

  3. Verification of Ensemble Forecasts for the New York City Operations Support Tool

    Science.gov (United States)

    Day, G.; Schaake, J. C.; Thiemann, M.; Draijer, S.; Wang, L.

    2012-12-01

    The New York City water supply system operated by the Department of Environmental Protection (DEP) serves nine million people. It covers 2,000 square miles of portions of the Catskill, Delaware, and Croton watersheds, and it includes nineteen reservoirs and three controlled lakes. DEP is developing an Operations Support Tool (OST) to support its water supply operations and planning activities. OST includes historical and real-time data, a model of the water supply system complete with operating rules, and lake water quality models developed to evaluate alternatives for managing turbidity in the New York City Catskill reservoirs. OST will enable DEP to manage turbidity in its unfiltered system while satisfying its primary objective of meeting the City's water supply needs, in addition to considering secondary objectives of maintaining ecological flows, supporting fishery and recreation releases, and mitigating downstream flood peaks. The current version of OST relies on statistical forecasts of flows in the system based on recent observed flows. To improve short-term decision making, plans are being made to transition to National Weather Service (NWS) ensemble forecasts based on hydrologic models that account for short-term weather forecast skill, longer-term climate information, as well as the hydrologic state of the watersheds and recent observed flows. To ensure that the ensemble forecasts are unbiased and that the ensemble spread reflects the actual uncertainty of the forecasts, a statistical model has been developed to post-process the NWS ensemble forecasts to account for hydrologic model error as well as any inherent bias and uncertainty in initial model states, meteorological data and forecasts. The post-processor is designed to produce adjusted ensemble forecasts that are consistent with the DEP historical flow sequences that were used to develop the system operating rules. A set of historical hindcasts that is representative of the real-time ensemble

  4. The Impact of Corps Flood Control Reservoirs in the June 2008 Upper Mississippi Flood

    Science.gov (United States)

    Charley, W. J.; Stiman, J. A.

    2008-12-01

    dissemination. The system uses precipitation and flow data, collected in real-time, along with forecasted flow from the National Weather Service to model and optimize reservoir operations and forecast downstream flows and stages, providing communities accurate and timely information to aid their flood-fighting. This involves integrating several simulation modeling programs, including HEC-HMS to forecast flows, HEC-ResSim to model reservoir operations and HEC-RAS to compute forecasted stage hydrographs. An inundation boundary and depth map of water in the flood plain can be calculated from the HEC-RAS results using ArcInfo. By varying future precipitation and releases, engineers can evaluate different "What if?" scenarios. The effectiveness of this tool and Corps reservoirs are examined.

  5. Forecasting Skill

    Science.gov (United States)

    1981-01-01

    indicated that forecasting experience has little relationship to forecasting performance. In the latter three studies, neophyte forecasters became... Europe . Within a few months after a new commander was assigned, this unit’s performance rose to first place in the theater and remained there

  6. Integrating a Storage Factor into R-NARX Neural Networks for Flood Forecasts

    Science.gov (United States)

    Chou, Po-Kai; Chang, Li-Chiu; Chang, Fi-John; Shih, Ban-Jwu

    2017-04-01

    Because mountainous terrains and steep landforms rapidly accelerate the speed of flood flow in Taiwan island, accurate multi-step-ahead inflow forecasts during typhoon events for providing reliable information benefiting the decision-makings of reservoir pre-storm release and flood-control operation are considered crucial and challenging. Various types of artificial neural networks (ANNs) have been successfully applied in hydrological fields. This study proposes a recurrent configuration of the nonlinear autoregressive with exogenous inputs (NARX) network, called R-NARX, with various effective inputs to forecast the inflows of the Feitsui Reservoir, a pivot reservoir for water supply to Taipei metropolitan in Taiwan, during typhoon periods. The proposed R-NARX is constructed based on the recurrent neural network (RNN), which is commonly used for modelling nonlinear dynamical systems. A large number of hourly rainfall and inflow data sets collected from 95 historical typhoon events in the last thirty years are used to train, validate and test the models. The potential input variables, including rainfall in previous time steps (one to six hours), cumulative rainfall, the storage factor and the storage function, are assessed, and various models are constructed with their reliability and accuracy being tested. We find that the previous (t-2) rainfall and cumulative rainfall are crucial inputs and the storage factor and the storage function would also improve the forecast accuracy of the models. We demonstrate that the R-NARX model not only can accurately forecast the inflows but also effectively catch the peak flow without adopting observed inflow data during the entire typhoon period. Besides, the model with the storage factor is superior to the model with the storage function, where its improvement can reach 24%. This approach can well model the rainfall-runoff process for the entire flood forecasting period without the use of observed inflow data and can provide

  7. Uncertainties in Forecasting Streamflow using Entropy Theory

    Science.gov (United States)

    Cui, H.; Singh, V. P.

    2017-12-01

    Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.

  8. Climate variability and sedimentation of a hydropower reservoir

    International Nuclear Information System (INIS)

    Riedel, M.

    2008-01-01

    As part of the relicensing of a large Hydroelectric Project in the central Appalachians, large scale watershed and reservoir sedimentation models were developed to forecast potential sedimentation scenarios. The GIS based watershed model was spatially explicit and calibrated to long term observed data. Potential socio/economic development scenarios were used to construct future watershed land cover scenarios. Climatic variability and potential change analysis were used to identify future climate regimes and shifts in precipitation and temperature patterns. Permutations of these development and climate changes were forecasted over 50 years and used to develop sediment yield regimes to the project reservoir. Extensive field work and reservoir survey, including current and wave instrumentation, were used to characterize the project watershed, rivers and reservoir hydrodynamics. A fully 3 dimensional hydrodynamic reservoir sedimentation model was developed for the project and calibrated to observed data. Hydrologic and sedimentation results from watershed forecasting provided boundary conditions for reservoir inputs. The calibrated reservoir model was then used to forecast changes in reservoir sedimentation and storage capacity under different future climate scenarios. Results indicated unique zones of advancing sediment deltas and temporary storage areas. Forecasted changes in reservoir bathymetry and sedimentation patterns were also developed for the various climate change scenarios. The warmer and wetter scenario produced sedimentation impacts similar to extensive development under no climate change. The results of these analyses are being used to develop collaborative watershed and soil conservation partnerships to reduce future soil losses and reservoir sedimentation from projected development. (author)

  9. Load forecasting

    International Nuclear Information System (INIS)

    Mak, H.

    1995-01-01

    Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence

  10. Improving reservoir history matching of EM heated heavy oil reservoirs via cross-well seismic tomography

    KAUST Repository

    Katterbauer, Klemens

    2014-01-01

    Enhanced recovery methods have become significant in the industry\\'s drive to increase recovery rates from oil and gas reservoirs. For heavy oil reservoirs, the immobility of the oil at reservoir temperatures, caused by its high viscosity, limits the recovery rates and strains the economic viability of these fields. While thermal recovery methods, such as steam injection or THAI, have extensively been applied in the field, their success has so far been limited due to prohibitive heat losses and the difficulty in controlling the combustion process. Electromagnetic (EM) heating via high-frequency EM radiation has attracted attention due to its wide applicability in different environments, its efficiency, and the improved controllability of the heating process. While becoming a promising technology for heavy oil recovery, its effect on overall reservoir production and fluid displacements are poorly understood. Reservoir history matching has become a vital tool for the oil & gas industry to increase recovery rates. Limited research has been undertaken so far to capture the nonlinear reservoir dynamics and significantly varying flow rates for thermally heated heavy oil reservoir that may notably change production rates and render conventional history matching frameworks more challenging. We present a new history matching framework for EM heated heavy oil reservoirs incorporating cross-well seismic imaging. Interfacing an EM heating solver to a reservoir simulator via Andrade’s equation, we couple the system to an ensemble Kalman filter based history matching framework incorporating a cross-well seismic survey module. With increasing power levels and heating applied to the heavy oil reservoirs, reservoir dynamics change considerably and may lead to widely differing production forecasts and increased uncertainty. We have shown that the incorporation of seismic observations into the EnKF framework can significantly enhance reservoir simulations, decrease forecasting

  11. Modelling of Hydropower Reservoir Variables for Energy Generation ...

    African Journals Online (AJOL)

    Efficient management of hydropower reservoir can only be realized when there is sufficient understanding of interactions existing between reservoir variables and energy generation. Reservoir inflow, storage, reservoir elevation, turbine release, net generating had, plant use coefficient, tail race level and evaporation losses ...

  12. Strategic Forecasting

    DEFF Research Database (Denmark)

    Duus, Henrik Johannsen

    2016-01-01

    as a rebirth of long range planning, albeit with new methods and theories. Firms should make the building of strategic forecasting capability a priority. Research limitations/implications: The article subdivides strategic forecasting into three research avenues and suggests avenues for further research efforts......Purpose: The purpose of this article is to present an overview of the area of strategic forecasting and its research directions and to put forward some ideas for improving management decisions. Design/methodology/approach: This article is conceptual but also informed by the author’s long contact...... and collaboration with various business firms. It starts by presenting an overview of the area and argues that the area is as much a way of thinking as a toolbox of theories and methodologies. It then spells out a number of research directions and ideas for management. Findings: Strategic forecasting is seen...

  13. Exposure Forecaster

    Data.gov (United States)

    U.S. Environmental Protection Agency — The Exposure Forecaster Database (ExpoCastDB) is EPA's database for aggregating chemical exposure information and can be used to help with chemical exposure...

  14. Efficacy and release rate of reservoir pheromone dispensers for simultaneous mating disruption of codling moth and oriental fruit moth (Lepidoptera: Tortricidae).

    Science.gov (United States)

    Stelinski, L L; Il'ichev, A L; Gut, L J

    2009-02-01

    Five formulations of controlled release, polyethylene tube dispensers of pheromone were evaluated during three field seasons for disruption of codling moth, Cydia pomonella (L.) (Lepidoptera: Tortricidae), and the oriental fruit moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae). Evaluations were conducted in replicated 4-ha plots of commercial apple in Michigan. Disruption of both C. pomonella and G. molesta male orientation to pheromone traps in plots treated with a dual-species formulation (Isomate CM/OFM TT), simultaneously releasing the pheromone components of both C. pomonella and G. molesta, was equivalent to that obtained by treating plots with separate formulations for each species (Isomate C Plus or Isomate C TT for C. pomonella and Isomate M Rosso for G. molesta) through mid-season. However, disruption efficacy of the dual-species formulation was significantly lower near the end of the season for G. molesta compared with the Isomate M Rosso formulation because of depletion of active ingredients and coincided with a slight increase in fruit injury. Effective disruption of C. pomonella and G. molesta also was obtained with a multispecies formulation (Isomate CM/OFM/LR) that releases the main pheromone components of C. pomonella, G. molesta, and several leafroller species. Each formulation type releasing (E,E)-8,10-dodecadien-1-ol (codlemone) also was found to release the E,Z- and Z,E-isomers of codlemone. Our data provide further evidence that simultaneous disruption of C. pomonella and G. molesta with dispensers releasing both species' pheromone components is possible; however, the controlled release formulations tested here require modification or postponed deployment coupled with early season control by other means to achieve season-long efficacy. Simultaneous disruption of several species with a single formulation will be economically advantageous in regions where control of multiple pests is needed given the need for hand application of this

  15. Groundwater Forecasting Optimization Pertain to Dam Removal

    Science.gov (United States)

    Brown, L.; Berthelote, A. R.

    2011-12-01

    There is increasing interest in removing dams due to changing ecological and societal values. Groundwater recharge rate is closely connected to reservoir presence or absence. With the removal of dams and their associated reservoirs, reductions in groundwater levels are likely to impact water supplies for domestic, industrial and agricultural use. Therefore accessible economic and time effective tools to forecast groundwater level declines with acceptable uncertainty following dam removals are critical for public welfare and healthy regional economies. These tools are also vital to project planning and provide beneficial information for restoration and remediation managements. The standard tool for groundwater forecasting is 3D Numerical modeling. Artificial Neural Networks (ANNs) may be an alternative tool for groundwater forecasting pertain to dam removal. This project compared these two tools throughout the Milltown Dam removal in Western Montana over a five year period. It was determined that ANN modeling had equal or greater accuracy for groundwater forecasting with far less effort and cost involved.

  16. Generalized martingale model of the uncertainty evolution of streamflow forecasts

    Science.gov (United States)

    Zhao, Tongtiegang; Zhao, Jianshi; Yang, Dawen; Wang, Hao

    2013-07-01

    Streamflow forecasts are dynamically updated in real-time, thus facilitating a process of forecast uncertainty evolution. Forecast uncertainty generally decreases over time and as more hydrologic information becomes available. The process of forecasting and uncertainty updating can be described by the martingale model of forecast evolution (MMFE), which formulates the total forecast uncertainty of a streamflow in one future period as the sum of forecast improvements in the intermediate periods. This study tests the assumptions, i.e., unbiasedness, Gaussianity, temporal independence, and stationarity, of MMFE using real-world streamflow forecast data. The results show that (1) real-world forecasts can be biased and tend to underestimate the actual streamflow, and (2) real-world forecast uncertainty is non-Gaussian and heavy-tailed. Based on these statistical tests, this study proposes a generalized martingale model GMMFE for the simulation of biased and non-Gaussian forecast uncertainties. The new model combines the normal quantile transform (NQT) with MMFE to formulate the uncertainty evolution of real-world streamflow forecasts. Reservoir operations based on a synthetic forecast by GMMFE illustrates that applications of streamflow forecasting facilitate utility improvements and that special attention should be focused on the statistical distribution of forecast uncertainty.

  17. Forecasting metal prices: Do forecasters herd?

    DEFF Research Database (Denmark)

    Pierdzioch, C.; Rulke, J. C.; Stadtmann, G.

    2013-01-01

    We analyze more than 20,000 forecasts of nine metal prices at four different forecast horizons. We document that forecasts are heterogeneous and report that anti-herding appears to be a source of this heterogeneity. Forecaster anti-herding reflects strategic interactions among forecasters...

  18. Carbon dioxide emissions from the tropical Dowleiswaram Reservoir on the Godavari River, Southeast of India

    Digital Repository Service at National Institute of Oceanography (India)

    Prasad, M.H.K.; Sarma, V.V.S.S.; Sarma, V.V.; Krishna, M.S.; Reddy, N.P.C.

    carbon to the reservoir. In addition to this, ground water exchange also contributes significantly to the inorganic carbon pool in the reservoir. Nutrients released due to decomposition of organic matter in the reservoir supports both autotrophic...

  19. Forecasting contaminant concentrations: Spills in the White Oak Creek Basin

    International Nuclear Information System (INIS)

    Borders, D.M.; Hyndman, D.W.; Huff, D.D.

    1987-01-01

    The Streamflow Synthesis and Reservoir Regulation (SSARR) model has been installed and sufficiently calibrated for use in managing accidental release of contaminants in surface waters of the White Oak Creek (WOC) watershed at ORNL. The model employs existing watershed conditions, hydrologic parameters representing basin response to precipitation, and a Quantitative Precipitation Forecast (QPF) to predict variable flow conditions throughout the basin. Natural runoff from each of the hydrologically distinct subbasins is simulated and added to specified plant and process water discharges. The resulting flows are then routed through stream reaches and eventually to White Oak Lake (WOL), which is the outlet from the WOC drainage basin. In addition, the SSARR model is being used to simulate change in storage volumes and pool levels in WOL, and most recently, routing characteristics of contaminant spills through WOC and WOL. 10 figs

  20. Rainfall forecast in the Upper Mahaweli basin in Sri Lanka using RegCM model

    Science.gov (United States)

    Muhammadh, K. M.; Mafas, M. M. M.; Weerakoon, S. B.

    2017-04-01

    The Upper Mahaweli basin is the upper most sub basin of 788 km2 in size above Polgolla barrage in the Mahaweli River, the longest river in Sri Lanka which starts from the central hills of the island and drains to the sea at the North-east coast. Rainfall forecast in the Upper Mahaweli basin is important for issuing flood warning in the river downstream of the reservoirs, landslide warning in the settlements in hilly areas. Anticipatory water management in the basin including reservoir operations, barrage gate operation for releasing water for irrigation and flood control also require reliable rainfall and runoff prediction in the sub basin. In this study, the Regional Climate Model (RegCM V4.4.5.11) is calibrated for the basin to dynamically downscale reanalysis weather data of Global Climate Model (GCM) to forecast the rainfall in the basin. Observed rainfalls at gauging stations within the basin were used for model calibration and validation. The observed rainfall data was analysed using ARC GIS and the output of RegCM was analysed using GrADS tool. The output of the model and the observed precipitation were obtained on grids of size 0.1 degrees and the accuracy of the predictions were analysed using RMSE and Mean Model Absolute Error percentage (MAME %). The predictions by the calibrated RegCM model for the basin is shown to be satisfactory. The model is a useful tool for rainfall forecast in the Upper Mahaweli River basin.

  1. Seasonal fire danger forecasts for the USA

    Science.gov (United States)

    J. Roads; F. Fujioka; S. Chen; R. Burgan

    2005-01-01

    The Scripps Experimental Climate Prediction Center has been making experimental, near-real-time, weekly to seasonal fire danger forecasts for the past 5 years. US fire danger forecasts and validations are based on standard indices from the National Fire Danger Rating System (DFDRS), which include the ignition component (IC), energy release component (ER), burning...

  2. Multi Data Reservoir History Matching using the Ensemble Kalman Filter

    KAUST Repository

    Katterbauer, Klemens

    2015-05-01

    Reservoir history matching is becoming increasingly important with the growing demand for higher quality formation characterization and forecasting and the increased complexity and expenses for modern hydrocarbon exploration projects. History matching has long been dominated by adjusting reservoir parameters based solely on well data whose spatial sparse sampling has been a challenge for characterizing the flow properties in areas away from the wells. Geophysical data are widely collected nowadays for reservoir monitoring purposes, but has not yet been fully integrated into history matching and forecasting fluid flow. In this thesis, I present a pioneering approach towards incorporating different time-lapse geophysical data together for enhancing reservoir history matching and uncertainty quantification. The thesis provides several approaches to efficiently integrate multiple geophysical data, analyze the sensitivity of the history matches to observation noise, and examine the framework’s performance in several settings, such as the Norne field in Norway. The results demonstrate the significant improvements in reservoir forecasting and characterization and the synergy effects encountered between the different geophysical data. In particular, the joint use of electromagnetic and seismic data improves the accuracy of forecasting fluid properties, and the usage of electromagnetic data has led to considerably better estimates of hydrocarbon fluid components. For volatile oil and gas reservoirs the joint integration of gravimetric and InSAR data has shown to be beneficial in detecting the influx of water and thereby improving the recovery rate. Summarizing, this thesis makes an important contribution towards integrated reservoir management and multiphysics integration for reservoir history matching.

  3. A source classification framework supporting pollutant source mapping, pollutant release prediction, transport and load forecasting, and source control planning for urban environments

    DEFF Research Database (Denmark)

    Lützhøft, Hans-Christian Holten; Donner, Erica; Wickman, Tonie

    2012-01-01

    for this purpose. Methods Existing source classification systems were examined by a multidisciplinary research team, and an optimised SCF was developed. The performance and usability of the SCF were tested using a selection of 25 chemicals listed as priority pollutants in Europe. Results The SCF is structured...... in the form of a relational database and incorporates both qualitative and quantitative source classification and release data. The system supports a wide range of pollution monitoring and management applications. The SCF functioned well in the performance test, which also revealed important gaps in priority...

  4. Utilizing Climate Forecasts for Improving Water and Power Systems Coordination

    Science.gov (United States)

    Arumugam, S.; Queiroz, A.; Patskoski, J.; Mahinthakumar, K.; DeCarolis, J.

    2016-12-01

    Climate forecasts, typically monthly-to-seasonal precipitation forecasts, are commonly used to develop streamflow forecasts for improving reservoir management. Irrespective of their high skill in forecasting, temperature forecasts in developing power demand forecasts are not often considered along with streamflow forecasts for improving water and power systems coordination. In this study, we consider a prototype system to analyze the utility of climate forecasts, both precipitation and temperature, for improving water and power systems coordination. The prototype system, a unit-commitment model that schedules power generation from various sources, is considered and its performance is compared with an energy system model having an equivalent reservoir representation. Different skill sets of streamflow forecasts and power demand forecasts are forced on both water and power systems representations for understanding the level of model complexity required for utilizing monthly-to-seasonal climate forecasts to improve coordination between these two systems. The analyses also identify various decision-making strategies - forward purchasing of fuel stocks, scheduled maintenance of various power systems and tradeoff on water appropriation between hydropower and other uses - in the context of various water and power systems configurations. Potential application of such analyses for integrating large power systems with multiple river basins is also discussed.

  5. Communicating uncertainty in hydrological forecasts: mission impossible?

    Science.gov (United States)

    Ramos, Maria-Helena; Mathevet, Thibault; Thielen, Jutta; Pappenberger, Florian

    2010-05-01

    Cascading uncertainty in meteo-hydrological modelling chains for forecasting and integrated flood risk assessment is an essential step to improve the quality of hydrological forecasts. Although the best methodology to quantify the total predictive uncertainty in hydrology is still debated, there is a common agreement that one must avoid uncertainty misrepresentation and miscommunication, as well as misinterpretation of information by users. Several recent studies point out that uncertainty, when properly explained and defined, is no longer unwelcome among emergence response organizations, users of flood risk information and the general public. However, efficient communication of uncertain hydro-meteorological forecasts is far from being a resolved issue. This study focuses on the interpretation and communication of uncertain hydrological forecasts based on (uncertain) meteorological forecasts and (uncertain) rainfall-runoff modelling approaches to decision-makers such as operational hydrologists and water managers in charge of flood warning and scenario-based reservoir operation. An overview of the typical flow of uncertainties and risk-based decisions in hydrological forecasting systems is presented. The challenges related to the extraction of meaningful information from probabilistic forecasts and the test of its usefulness in assisting operational flood forecasting are illustrated with the help of two case-studies: 1) a study on the use and communication of probabilistic flood forecasting within the European Flood Alert System; 2) a case-study on the use of probabilistic forecasts by operational forecasters from the hydroelectricity company EDF in France. These examples show that attention must be paid to initiatives that promote or reinforce the active participation of expert forecasters in the forecasting chain. The practice of face-to-face forecast briefings, focusing on sharing how forecasters interpret, describe and perceive the model output forecasted

  6. Development of gas and gas condensate reservoirs

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-01

    In the study of gas reservoir development, the first year topics are restricted on reservoir characterization. There are two types of reservoir characterization. One is the reservoir formation characterization and the other is the reservoir fluid characterization. For the reservoir formation characterization, calculation of conditional simulation was compared with that of unconditional simulation. The results of conditional simulation has higher confidence level than the unconditional simulation because conditional simulation considers the sample location as well as distance correlation. In the reservoir fluid characterization, phase behavior calculations revealed that the component grouping is more important than the increase of number of components. From the liquid volume fraction with pressure drop, the phase behavior of reservoir fluid can be estimated. The calculation results of fluid recombination, constant composition expansion, and constant volume depletion are matched very well with the experimental data. In swelling test of the reservoir fluid with lean gas, the accuracy of dew point pressure forecast depends on the component characterization. (author). 28 figs., 10 tabs.

  7. Sampling from stochastic reservoir models constrained by production data

    Energy Technology Data Exchange (ETDEWEB)

    Hegstad, Bjoern Kaare

    1997-12-31

    When a petroleum reservoir is evaluated, it is important to forecast future production of oil and gas and to assess forecast uncertainty. This is done by defining a stochastic model for the reservoir characteristics, generating realizations from this model and applying a fluid flow simulator to the realizations. The reservoir characteristics define the geometry of the reservoir, initial saturation, petrophysical properties etc. This thesis discusses how to generate realizations constrained by production data, that is to say, the realizations should reproduce the observed production history of the petroleum reservoir within the uncertainty of these data. The topics discussed are: (1) Theoretical framework, (2) History matching, forecasting and forecasting uncertainty, (3) A three-dimensional test case, (4) Modelling transmissibility multipliers by Markov random fields, (5) Up scaling, (6) The link between model parameters, well observations and production history in a simple test case, (7) Sampling the posterior using optimization in a hierarchical model, (8) A comparison of Rejection Sampling and Metropolis-Hastings algorithm, (9) Stochastic simulation and conditioning by annealing in reservoir description, and (10) Uncertainty assessment in history matching and forecasting. 139 refs., 85 figs., 1 tab.

  8. Sources of seasonal water-supply forecast skill in the western US

    Science.gov (United States)

    Dettinger, Michael

    2007-01-01

    Many water supplies in the western US depend on water that is stored in snowpacks and reservoirs during the cool, wet seasons for release and use in the following warm seasons. Managers of these water supplies must decide each winter how much water will be available in subsequent seasons so that they can proactively capture and store water and can make reliable commitments for later deliveries. Long-lead water-supply forecasts are thus important components of water managers' decisionmaking. Present-day operational water-supply forecasts draw skill from observations of the amount of water in upland snowpacks, along with estimates of the amount of water otherwise available (often via surrogates for antecedent precipitation, soil moisture or baseflows). Occasionally, the historical hydroclimatic influences of various global climate conditions may be factored in to forecasts. The relative contributions of (potential) forecast skill for January-March and April-July seasonal water- supply availability from these sources are mapped across the western US as lag correlations among elements of the inputs and outputs from a physically based, regional land-surface hydrology model of the western US from 1950-1999. Information about snow-water contents is the most valuable predictor for forecasts made through much of the cool-season but, before the snows begin to fall, indices of El Nino-Southern Oscillation are the primary source of whatever meager skill is available. The contributions to forecast skill made available by knowledge of antecedent flows (a traditional predictor) and soil moisture at the time the long-lead forecast is issued are compared, to gain insights into the potential usefulness of new soil-moisture monitoring options in the region. When similar computations are applied to simulated flows under historical conditions, but with a uniform +2°C warming imposed, the widespread diminution of snowpacks reduces forecast skills, although skill contributed by measures

  9. Evaluating the Implications of Climate Phenomenon Indices in Supporting Reservoir Operation Using the Artificial Neural Network and Decision-Tree Methods: A Case Study on Trinity Lake in Northern California

    Science.gov (United States)

    Yang, T.; Akbari Asanjan, A.; Gao, X.; Sorooshian, S.

    2016-12-01

    Reservoirs are fundamental human-built infrastructures that collect, store, and deliver fresh surface water in a timely manner for all kinds of purposes, including residential and industrial water supply, flood control, hydropower, and irrigation, etc. Efficient reservoir operation requires that policy makers and operators understand how reservoir inflows, available storage, and discharges are changing under different climatic conditions. Over the last decade, the uses of Artificial Intelligence and Data Mining (AI & DM) techniques in assisting reservoir management and seasonal forecasts have been increasing. Therefore, in this study, two distinct AI & DM methods, Artificial Neural Network (ANN) and Random Forest (RF), are employed and compared with respect to their capabilities of predicting monthly reservoir inflow, managing storage, and scheduling reservoir releases. A case study on Trinity Lake in northern California is conducted using long-term (over 50 years) reservoir operation records and 17 known climate phenomenon indices, i.e. PDO and ENSO, etc., as predictors. Results show that (1) both ANN and RF are capable of providing reasonable monthly reservoir storage, inflow, and outflow prediction with satisfactory statistics, and (2) climate phenomenon indices are useful in assisting monthly or seasonal forecasts of reservoir inflow and outflow. It is also found that reservoir storage has a consistent high autocorrelation effect, while inflow and outflow are more likely to be influenced by climate conditions. Using a Gini diversity index, RF method identifies that the reservoir discharges are associated with Southern Oscillation Index (SOI) and reservoir inflows are influenced by multiple climate phenomenon indices during different seasons. Furthermore, results also show that, during the winter season, reservoir discharges are controlled by the storage level for flood-control purposes, while, during the summer season, the flood-control operation is not as

  10. Magnetogram Forecast: An All-Clear Space Weather Forecasting System

    Science.gov (United States)

    Barghouty, Nasser; Falconer, David

    2015-01-01

    Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

  11. Integrating gravimetric and interferometric synthetic aperture radar data for enhancing reservoir history matching of carbonate gas and volatile oil reservoirs

    KAUST Repository

    Katterbauer, Klemens

    2016-08-25

    Reservoir history matching is assuming a critical role in understanding reservoir characteristics, tracking water fronts, and forecasting production. While production data have been incorporated for matching reservoir production levels and estimating critical reservoir parameters, the sparse spatial nature of this dataset limits the efficiency of the history matching process. Recently, gravimetry techniques have significantly advanced to the point of providing measurement accuracy in the microgal range and consequently can be used for the tracking of gas displacement caused by water influx. While gravity measurements provide information on subsurface density changes, i.e., the composition of the reservoir, these data do only yield marginal information about temporal displacements of oil and inflowing water. We propose to complement gravimetric data with interferometric synthetic aperture radar surface deformation data to exploit the strong pressure deformation relationship for enhancing fluid flow direction forecasts. We have developed an ensemble Kalman-filter-based history matching framework for gas, gas condensate, and volatile oil reservoirs, which synergizes time-lapse gravity and interferometric synthetic aperture radar data for improved reservoir management and reservoir forecasts. Based on a dual state-parameter estimation algorithm separating the estimation of static reservoir parameters from the dynamic reservoir parameters, our numerical experiments demonstrate that history matching gravity measurements allow monitoring the density changes caused by oil-gas phase transition and water influx to determine the saturation levels, whereas the interferometric synthetic aperture radar measurements help to improve the forecasts of hydrocarbon production and water displacement directions. The reservoir estimates resulting from the dual filtering scheme are on average 20%-40% better than those from the joint estimation scheme, but require about a 30% increase in

  12. Operational Streamflow Forecasts Development Using GCM Predicted Precipitation Fields

    Science.gov (United States)

    Arumugam, S.; Lall, U.

    2004-12-01

    Monthly updates of streamflow forecasts are required for deriving reservoir operation strategies as well as for quantifying surplus and shortfall for the allocated water contracts. In this study, an operational streamflow forecasts are developed using Atmospheric General Circulation Models (AGCM) predicted precipitation for managing the Angat Reservoir System, Philippines. The methodology employs principal components regression (PCR) for downscaling the AGCM predicted precipitation fields to monthly streamflow forecasts. The performance of this downscaling approach is analyzed with AGCM being forced using the observed sea surface temperature (SST) conditions as well under persisted SST conditions. The ability of downscaled streamflow forecasts in explaining the intraseasonal variability is also explored. Conditional distribution of streamflows obtained from the PCR downscaling approach is also compared with a simple, semi-parametric resampling algorithm that obtains ensembles of streamflow forecasts by identifying similar conditions in that season's climatic predictors state space.

  13. Bias correcting precipitation forecasts for extended-range skilful seasonal streamflow predictions

    OpenAIRE

    Crochemore, L.; Ramos, M.H.; Pappenberger, F.

    2016-01-01

    Meteorological centres make sustained efforts to provide seasonal forecasts that are increasingly skilful, which has the potential to also benefit streamflow forecasting. Seasonal streamflow forecasts can help to take anticipatory measures for a range of applications, such as water supply or hydropower reservoir operation and drought risk management. This study assesses the skill of seasonal precipitation and streamflow forecasts in France in order to provide insights into the way bias correc...

  14. ktup Terminal Aerodrome Forecast

    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    Data.gov (United States)

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    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kpkb Terminal Aerodrome Forecast

    Data.gov (United States)

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    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

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  4. katy Terminal Aerodrome Forecast

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  5. krdd Terminal Aerodrome Forecast

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  6. kabq Terminal Aerodrome Forecast

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    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. kbvi Terminal Aerodrome Forecast

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    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kiah Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kbzn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kfnt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kbpt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. koun Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kilm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. kspi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kclm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. kipl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kpbi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kgdv Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. krdg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kbgm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. kcmx Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kdls Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. koaj Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. krhi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. kbpk Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kcwa Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. pawg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kgfl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. pgwt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. khuf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. pabr Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kewn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kipt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. kpeq Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kdug Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. klbt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kcys Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. khio Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kflo Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. klaf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. kmlu Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kact Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. khob Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. ktcs Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. kdnl Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kmgw Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. kryy Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. kgtf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. kjax Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. ktvf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. kfat Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kink Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. kshv Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. pajn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kpna Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. ktph Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. ksux Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kcon Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kpnc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. kgsp Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  3. kgpt Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  4. kgcn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  5. kart Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  6. pagk Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  7. korf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  8. kpsm Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  9. kcre Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  10. krsw Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  11. papg Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  12. kblf Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  13. krdu Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  14. kluk Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  15. keed Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  16. kiwd Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  17. kttn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  18. kagc Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  19. kbmi Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  20. kapn Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  1. kgon Terminal Aerodrome Forecast

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TAF (terminal aerodrome forecast or terminal area forecast) is a format for reporting weather forecast information, particularly as it relates to aviation. TAFs are...

  2. Hydrological Analysis for Inflow Forecasting into Temengor Dam

    Science.gov (United States)

    Najid, MI; Sidek, LM; Hidayah, B.; Roseli, ZA

    2016-03-01

    These days, natural disaster such as flood is the main concern for hydrologists. One of solutions in understanding the reason of flood is by prediction of the event sooner than normal occurrence. One of the criteria is lead time or travel time that is important in the study of fresh waters and flood events. Therefore, estimation of lead or travel time for flood event can be beneficial primary information. The objective of this study is to estimate the lead time or travel time for outlet of Temengor dam in Malaysia. Tenaga Nasional Berhad (TNB) Sungai Perak dam operation has the main contribution on decision support for early water released and flood warning to authorities and locals resident for in the down streams area. For this study, hydrological analysis carried out will help to determine which years that give more rainfall contribution into the reservoir. Rainfall contribution of reservoir help to understanding rainfall distribution and peak discharge on that period. It also help for calibration of forecasting model system for better accuracy of flood hydrograph. There may be various methods to determine the rainfall contribution of catchment. The result has shown that, the rainfall contribution for Temengor catchment, is more on November in each year which is the monsoon season in Malaysia. TNB dam operational decision support systems can prepare and be more aware at this time for flood control and flood mitigation.

  3. Weather forecast

    CERN Document Server

    Courtier, P

    1994-02-07

    Weather prediction is performed using the numerical model of the atmosphere evolution.The evolution equations are derived from the Navier Stokes equation for the adiabatic part but the are very much complicated by the change of phase of water, the radiation porocess and the boundary layer.The technique used operationally is described. Weather prediction is an initial value problem and accurate initial conditions need to be specified. Due to the small number of observations available (105 ) as compared to the dimension of the model state variable (107),the problem is largely underdetermined. Techniques of optimal control and inverse problems are used and have been adapted to the large dimension of our problem. our problem.The at mosphere is a chaotic system; the implication for weather prediction is discussed. Ensemble prediction is used operationally and the technique for generating initial conditions which lead to a numerical divergence of the subsequent forecasts is described.

  4. Discharge Forecast Modeling project FY87 progress report, October 1, 1986--September 30, 1987

    Energy Technology Data Exchange (ETDEWEB)

    Borders, D.M.; Hyndman, D.W.; Railsback, S.F.

    1987-10-19

    This project originated as a result of the Strontium-90 Action Plan, a response to the abnormal release of radionuclides that occurred from White Oak Creek (WOC) during late November and early December 1985. Several notable problems became obvious during ORNL's response to this release: (1) no predetermined criteria existed for the operation of White Oak Dam (WOD) in response to spills, (2) the hydrodynamics of contaminant transport and dispersion within the WOC watershed and downstream were not adequately understood to support requests for modified reservoir releases, and (3) real-time data on streamflow, precipitation, and water quality within the watershed were not readily available in sufficient quantity and usable format. The modeling study was initiated to help address these problems. This report describes FY 87 accomplishments, including: improvements in data acquisition and evaluation; implementation and calibration of a model to forecast discharges of water and contaminants from the WOC watershed; implementation, documentation, and checking of a model to forecast concentrations of contaminants from WOC in the Clinch River; and three field studies that provide essential calibration data. Data from the field studies and user documentation of the Clinch River model are included as appendices to this report.

  5. Model based management of a reservoir system

    Energy Technology Data Exchange (ETDEWEB)

    Scharaw, B.; Westerhoff, T. [Fraunhofer IITB, Ilmenau (Germany). Anwendungszentrum Systemtechnik; Puta, H.; Wernstedt, J. [Technische Univ. Ilmenau (Germany)

    2000-07-01

    The main goals of reservoir management systems consist of prevention against flood water damages, the catchment of raw water and keeping all of the quality parameters within their limits besides controlling the water flows. In consideration of these goals a system model of the complete reservoir system Ohra-Schmalwasser-Tambach Dietharz was developed. This model has been used to develop optimized strategies for minimization of raw water production cost, for maximization of electrical energy production and to cover flood situations, as well. Therefore a proper forecast of the inflow to the reservoir from the catchment areas (especially flooding rivers) and the biological processes in the reservoir is important. The forecast model for the inflow to the reservoir is based on the catchment area model of Lorent and Gevers. It uses area precipitation, water supply from the snow cover, evapotranspiration and soil wetness data to calculate the amount of flow in rivers. The other aim of the project is to ensure the raw water quality using quality models, as well. Then a quality driven raw water supply will be possible. (orig.)

  6. A Time Domain Update Method for Reservoir History Matching of Electromagnetic Data

    KAUST Repository

    Katterbauer, Klemens

    2014-03-25

    The oil & gas industry has been the backbone of the world\\'s economy in the last century and will continue to be in the decades to come. With increasing demand and conventional reservoirs depleting, new oil industry projects have become more complex and expensive, operating in areas that were previously considered impossible and uneconomical. Therefore, good reservoir management is key for the economical success of complex projects requiring the incorporation of reliable uncertainty estimates for reliable production forecasts and optimizing reservoir exploitation. Reservoir history matching has played here a key role incorporating production, seismic, electromagnetic and logging data for forecasting the development of reservoirs and its depletion. With the advances in the last decade, electromagnetic techniques, such as crosswell electromagnetic tomography, have enabled engineers to more precisely map the reservoirs and understand their evolution. Incorporating the large amount of data efficiently and reducing uncertainty in the forecasts has been one of the key challenges for reservoir management. Computing the conductivity distribution for the field for adjusting parameters in the forecasting process via solving the inverse problem has been a challenge, due to the strong ill-posedness of the inversion problem and the extensive manual calibration required, making it impossible to be included into an efficient reservoir history matching forecasting algorithm. In the presented research, we have developed a novel Finite Difference Time Domain (FDTD) based method for incorporating electromagnetic data directly into the reservoir simulator. Based on an extended Archie relationship, EM simulations are performed for both forecasted and Porosity-Saturation retrieved conductivity parameters being incorporated directly into an update step for the reservoir parameters. This novel direct update method has significant advantages such as that it overcomes the expensive and ill

  7. Risk Analysis of Extreme Rainfall Effects on the Shihmen Reservoir

    Science.gov (United States)

    Ho, Y.; Lien, W.; Tung, C.

    2009-12-01

    Typhoon Morakot intruded Taiwan during 7th and 8th of August 2009, brought about 2,700 mm of total rainfall which caused serious flood and debris to the southern region of Taiwan. One of the serious flooded areas is in the downstream of Zengwen reservoir. People believed that the large amount of floodwater released from Zengwen reservoir led to the severe inundation. Therefore, the Shihmen reservoir is one of the important reservoirs in northern Taiwan. The Taipei metropolis, which is in downstream of Shihmen reservoir, is the political and economical center of Taiwan. If heavy rainfall as those brought by Typhoon Marakot falls in the Shihmen reservoir watershed, it may create a bigger disaster. This study focused on the impacts of a typhoon, like Morakot, in Shihmen reservoir. The hydrological model is used to simulate the reservoir inflows under different rainfall conditions. The reservoir water balance model is developed to calculate reservoir’s storage and outflows under the inflows and operational rules. The ability of flood mitigation is also evaluated. Besides, the released floodwater from reservoir and the inflows from different tributaries are used to determine whether or not the river stage will overtop levee. Also, the maximum released floodwater and other inflows which could lead to damages will be stated. Lastly, the criteria of rainfall conditions and initial stages of reservoir will be analyzed in this study.

  8. Gambling scores for earthquake predictions and forecasts

    Science.gov (United States)

    Zhuang, Jiancang

    2010-04-01

    This paper presents a new method, namely the gambling score, for scoring the performance earthquake forecasts or predictions. Unlike most other scoring procedures that require a regular scheme of forecast and treat each earthquake equally, regardless their magnitude, this new scoring method compensates the risk that the forecaster has taken. Starting with a certain number of reputation points, once a forecaster makes a prediction or forecast, he is assumed to have betted some points of his reputation. The reference model, which plays the role of the house, determines how many reputation points the forecaster can gain if he succeeds, according to a fair rule, and also takes away the reputation points betted by the forecaster if he loses. This method is also extended to the continuous case of point process models, where the reputation points betted by the forecaster become a continuous mass on the space-time-magnitude range of interest. We also calculate the upper bound of the gambling score when the true model is a renewal process, the stress release model or the ETAS model and when the reference model is the Poisson model.

  9. Robustness of a multiple-use reservoir to seasonal runoff shifts associated with climate change

    International Nuclear Information System (INIS)

    Lettenmaier, D.P.; Brettman, K.L.

    1990-05-01

    Although much remains to be learned about long-term climate change associated with anthropogenic increases in concentrations of the so-called ''greenhouse gases,'' such as carbon dioxide and methane, there is a general consensus that some global warming will result from past and present emissions. In the western United States, the dominant hydrologic effect of such warming, aside from any accompanying changes in precipitation, would be to reduce winter snow accumulations in mountainous headwaters regions. To assess the robustness of reservoir operation to such shifts in seasonal runoff, simulations were developed of monthly runoff for the American River, Washington, using the National Weather Service River Forecast System. The American River is presently unregulated; however, we tested the performance of hypothetical reservoirs with capacity of 0.25 and 0.50 of the mean annual flow for a range of annual temperature changes from 0.0 (present climate) to 4.0 degree C. We considered a multiple-purpose reservoir system operated for water supply ad hydropower, with minimum releases required for fisheries enhancement. In addition to evaluating the sensitivity of water supply, low flow, and hydropower performance using a heuristic operating rule, the relative performance of the system under present and altered climates was evaluated using an optimization algorithm, extended linear quadratic Gaussian control. This paper reports the results of hydrologic simulations for the American River, Washington. 13 refs., 8 figs

  10. Fluvial facies reservoir productivity prediction method based on principal component analysis and artificial neural network

    Directory of Open Access Journals (Sweden)

    Pengyu Gao

    2016-03-01

    Full Text Available It is difficult to forecast the well productivity because of the complexity of vertical and horizontal developments in fluvial facies reservoir. This paper proposes a method based on Principal Component Analysis and Artificial Neural Network to predict well productivity of fluvial facies reservoir. The method summarizes the statistical reservoir factors and engineering factors that affect the well productivity, extracts information by applying the principal component analysis method and approximates arbitrary functions of the neural network to realize an accurate and efficient prediction on the fluvial facies reservoir well productivity. This method provides an effective way for forecasting the productivity of fluvial facies reservoir which is affected by multi-factors and complex mechanism. The study result shows that this method is a practical, effective, accurate and indirect productivity forecast method and is suitable for field application.

  11. Parâmetros de projeto de microrreservatório, de pavimentos permeáveis e de previsão de enchentes urbanas Design parameters for micro reservoir, for porous pavements and for forecast of urban flow

    Directory of Open Access Journals (Sweden)

    Lourenço Leme da Costa Junior

    2006-03-01

    Full Text Available Esta pesquisa teve como objetivo principal avaliar o uso e a ocupação dos lotes de uma área urbana e analisar as possibilidades de uso das medidas de controle local de inundação: microrreservatórios de detenção e pavimentos permeáveis. A área de estudo foi a Sub-bacia Hidrográfica Urbana da Ponte Seca (SBHUPS, em Jaboticabal - SP. O total de lotes da SBHUPS é 1.777. Avaliaram-se 164 lotes, por amostragem aleatória estratificada proporcional de acordo com a área. Utilizou-se de levantamento de campo, informações cadastrais e entrevistas com moradores para a coleta dos dados. Caracterizaram-se a área livre, área impermeabilizada, área construída, taxa de ocupação (TO, taxa de ocupação e impermeabilização (TOI, tipo de solo, nível do lençol freático e topografia de cada lote amostrado. Argüiram-se os moradores sobre a aceitação do uso das medidas. Estes parâmetros foram usados para avaliar as possibilidades de suas implantações e, então, avaliaram-se os custos. Os valores médios por estrato indicam que a TO e a TOI decrescem com o aumento da área do lote. Obtiveram-se relações entre TO e área do lote, TOI e área do lote e TO e TOI representadas por equações, cujos coeficientes de determinação ficaram acima de 0,96. O uso dos microrreservatórios de detenção, como medida de controle, foi limitado pela aceitação dos moradores, a 82,8% dos lotes. O uso do pavimento permeável foi restringido pelos parâmetros área livre e aceitação dos moradores.This report had the main objective to evaluate the use and the occupation of the plot from an urban hydrographic basin and to analyze the possibilities at the use of measures of local control of floods, such as micro reservoir of detention and porous pavements. The area studied was the urban hydrographic basin from "Ponte Seca" (SBHUPS, on Jaboticabal City, São Paulo. The total of plots on BHUPS is 1.777. During the research it was analyzed 164 plots, using

  12. a system approach to the long term forecasting of the climat data in baikal region

    Science.gov (United States)

    Abasov, N.; Berezhnykh, T.

    2003-04-01

    that take place in the Baikal, the Bratsk and Ust-Ilimsk reservoirs: long low-water periods and sudden periods of extremely high water levels. For example, low-water periods, observed in the reservoirs of the Angara cascade can be classified under four risk categories : 1 - acceptable (negligible reduction of electric power generation by hydropower plants; certain difficulty in meeting environmental and navigation requirements); 2 - significant (substantial reduction of electric power generation by hydropower plants; certain restriction on water releases for navigation; violation of environmental requirements in some years); 3 - emergency (big losses in electric power generation; limited electricity supply to large consumers; significant restriction of water releases for navigation; threat of exposure of drinkable water intake works; violation of environmental requirements for a number of years); 4 - catastrophic (energy crisis; social crisis exposure of drinkable water intake works; termination of navigation; environmental catastrophe). Management of energy systems consists in operative, many-year regulation and perspective planning and has to take into account the analysis of operative data (water reserves in reservoirs), long-term statistics and relations among natural processes and also forecasts - short-term (for a day, week, decade), long-term and/or super-long-term (from a month to several decades). Such natural processes as water inflow to reservoirs, air temperatures during heating periods depend in turn on external factors: prevailing types of atmospheric circulation, intensity of the 11- and 22-year cycles of solar activity, volcanic activity, interaction between the ocean and atmosphere, etc. Until recently despite the formed scientific schools on long-term forecasting (I.P.Druzhinin, A.P.Reznikhov) the energy system management has been based on specially drawn dispatching schedules and long-term hydrometeorological forecasts only without attraction of

  13. Fuel cycle forecasting - there are forecasts and there are forecasts

    International Nuclear Information System (INIS)

    Puechl, K.H.

    1975-01-01

    The FORECAST-NUCLEAR computer program described recognizes that forecasts are made to answer a variety of questions and, therefore, that no single forecast is universally appropriate. Also, it recognizes that no two individuals will completely agree as to the input data that are appropriate for obtaining an answer to even a single simple question. Accordingly, the program was written from a utilitarian standpoint: it allows working with multiple projections; data inputting is simple to allow game-playing; computation time is short to minimize the cost of 'what if' assessements; and detail is internally carried to allow meaningful analysis. (author)

  14. Improving Software Reliability Forecasting

    NARCIS (Netherlands)

    Burtsy, Bernard; Albeanu, Grigore; Boros, Dragos N.; Popentiu, Florin; Nicola, V.F.

    1996-01-01

    This work investigates some methods for software reliability forecasting. A supermodel is presented as a suited tool for prediction of reliability in software project development. Also, times series forecasting for cumulative interfailure time is proposed and illustrated.

  15. Does Consumer Confidence Forecast Household Spending? The Euro Area Case

    OpenAIRE

    Dion, David Pascal

    2006-01-01

    The following analysis, based on error correction models, suggests that consumer confidence, together with traditional macroeconomic variables, contains a forecasting and explicative power on consumption. By including consumer confidence in a consumption function, consumer confidence releases a significant coefficient. Such a confidence-augmented consumption model provides good forecasting results.

  16. Global Energy Forecasting Competition 2012

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2014-01-01

    The Global Energy Forecasting Competition (GEFCom2012) attracted hundreds of participants worldwide, who contributed many novel ideas to the energy forecasting field. This paper introduces both tracks of GEFCom2012, hierarchical load forecasting and wind power forecasting, with details...

  17. Improved water allocation utilizing probabilistic climate forecasts: Short-term water contracts in a risk management framework

    Science.gov (United States)

    Sankarasubramanian, A.; Lall, Upmanu; Souza Filho, Francisco Assis; Sharma, Ashish

    2009-11-01

    Probabilistic, seasonal to interannual streamflow forecasts are becoming increasingly available as the ability to model climate teleconnections is improving. However, water managers and practitioners have been slow to adopt such products, citing concerns with forecast skill. Essentially, a management risk is perceived in "gambling" with operations using a probabilistic forecast, while a system failure upon following existing operating policies is "protected" by the official rules or guidebook. In the presence of a prescribed system of prior allocation of releases under different storage or water availability conditions, the manager has little incentive to change. Innovation in allocation and operation is hence key to improved risk management using such forecasts. A participatory water allocation process that can effectively use probabilistic forecasts as part of an adaptive management strategy is introduced here. Users can express their demand for water through statements that cover the quantity needed at a particular reliability, the temporal distribution of the "allocation," the associated willingness to pay, and compensation in the event of contract nonperformance. The water manager then assesses feasible allocations using the probabilistic forecast that try to meet these criteria across all users. An iterative process between users and water manager could be used to formalize a set of short-term contracts that represent the resulting prioritized water allocation strategy over the operating period for which the forecast was issued. These contracts can be used to allocate water each year/season beyond long-term contracts that may have precedence. Thus, integrated supply and demand management can be achieved. In this paper, a single period multiuser optimization model that can support such an allocation process is presented. The application of this conceptual model is explored using data for the Jaguaribe Metropolitan Hydro System in Ceara, Brazil. The performance

  18. A Climate Service Prototype for the Hydropower Industry: Using a Multi-Model Approach to Improve Seasonal Forecasts of the Spring Flood Period in Sweden.

    Science.gov (United States)

    Foster, K. L.; Uvo, C. B.; Olsson, J.; Bosshard, T.; Berg, P.; Södling, J.

    2015-12-01

    The Ångerman River is Sweden's third largest river with over 50 regulation reservoirs, 42 hydropower stations and accounts for nearly 20% of the country's hydropower production. In seasonally snow covered regions, such as the Ångerman river system, the winter precipitation is often temporarily stored in the snow pack during the colder months and released over a relatively short period of intense flows during in the warmer months. These spring flood events dominate the hydrology in these regions and as such reliable hydrological forecasts of these events are in great demand. However, it has been shown that the spread in the forecast error of operational hydrological forecasts in Sweden have not changed significantly over the last 25 years (Arheimer et al., 2012). Building on previous work by Foster et al. (2011) and Olsson et al. (2015), a multi-model hydrological seasonal forecast prototype has been developed for the Ångerman river system and applied to the spring flood season. The prototype employs different model-chain approaches: (1) a climatological forecast, where historical observations for the same period are selected to run the hydrological model, (2) a reduced historical ensemble, where analogue years from the historical observations dataset are selected to run the hydrological model, (3) using bias corrected meteorological seasonal forecasts from the ECMWF to force the hydrological model, and (4) statistical downscaling large-scale circulation variables from ECMWF seasonal forecasts directly to accumulated discharge. These different chains are combined into a multi-model ensemble forecast. The different approaches and the multi-model prototype are evaluated against the state-of-the-art operational system for the spring flood season for the period 1981-2014 in the Ångerman river system. References Arheimer, B., Lindström, G., and Olsson, J.: A systematic review of sensitivities in the Swedish flood-forecasting system, Atmos. Res., 100, 275-284, 2011

  19. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren Ladegaard

    2006-01-01

    , the difference between actual and forecasted traffic is more than +-20%; for 25% of road projects, the difference is larger than +-40%. Forecasts for roads are more accurate and more balanced than for rail, with no significant difference between the frequency of inflated versus deflated forecasts. But for both...

  20. Managing Sales Forecasters

    NARCIS (Netherlands)

    L.P. de Bruijn (Bert); Ph.H.B.F. Franses (Philip Hans)

    2012-01-01

    textabstractA Forecast Support System (FSS), which generates sales forecasts, is a sophisticated business analytical tool that can help to improve targeted business decisions. Many companies use such a tool, although at the same time they may allow managers to quote their own forecasts. These sales

  1. Limnology of the Huesna reservoir, Spain; Limnologia del embalse del Huesna

    Energy Technology Data Exchange (ETDEWEB)

    Medina Vela, M.; Diaz Borrego, M. D.; Puente Guisado, M. L.; Burraco Barrera, C. [Consorcio del Huesna. Sevilla (Spain)

    1999-07-01

    The limnological study of a reservoir is based on the periodic monitoring of a number of physicochemical and biological parameters. These data together with data on climate change and turnover rate enable us to determine reservoir water quality and forecast behaviour. Knowledge of the ecology of reservoirs, used for drinking water supply, is essential to be able to take water from depth, with the best characteristics for treatment there by reducing treatment cost. The study shows the steps followed to initiate a study of de Huesca reservoir and complete the first year. No previous data exist from the reservoir because it only started being used recently. (Author) 8 refs.

  2. Formation and forecast of the daily price of the electric power in the chain Nare-Guatape-San Carlos

    International Nuclear Information System (INIS)

    Romero, Alejandro; Carvajal, Luis

    2003-01-01

    This work shows three different methodologies for the understanding and forecast of the electric energy prices in the chain Nare - Guatape - San Carlos: lineal multivariate model, autoregressive deterministic model and Fourier series decomposition. The electric energy price depends basically of the reservoir level and river flow, not only its own but the reservoir down and up, waters. About prices forecast, they can be modeled with an autoregressive process. Prices forecast follows the tendency and captures with acceptable precision the maximum prices due especially to the low hydrology and price variability for daily and weekly regulation reservoirs

  3. Reservoir fisheries of Asia

    International Nuclear Information System (INIS)

    Silva, S.S. De.

    1990-01-01

    At a workshop on reservoir fisheries research, papers were presented on the limnology of reservoirs, the changes that follow impoundment, fisheries management and modelling, and fish culture techniques. Separate abstracts have been prepared for three papers from this workshop

  4. Large reservoirs: Chapter 17

    Science.gov (United States)

    Miranda, Leandro E.; Bettoli, Phillip William

    2010-01-01

    Large impoundments, defined as those with surface area of 200 ha or greater, are relatively new aquatic ecosystems in the global landscape. They represent important economic and environmental resources that provide benefits such as flood control, hydropower generation, navigation, water supply, commercial and recreational fisheries, and various other recreational and esthetic values. Construction of large impoundments was initially driven by economic needs, and ecological consequences received little consideration. However, in recent decades environmental issues have come to the forefront. In the closing decades of the 20th century societal values began to shift, especially in the developed world. Society is no longer willing to accept environmental damage as an inevitable consequence of human development, and it is now recognized that continued environmental degradation is unsustainable. Consequently, construction of large reservoirs has virtually stopped in North America. Nevertheless, in other parts of the world construction of large reservoirs continues. The emergence of systematic reservoir management in the early 20th century was guided by concepts developed for natural lakes (Miranda 1996). However, we now recognize that reservoirs are different and that reservoirs are not independent aquatic systems inasmuch as they are connected to upstream rivers and streams, the downstream river, other reservoirs in the basin, and the watershed. Reservoir systems exhibit longitudinal patterns both within and among reservoirs. Reservoirs are typically arranged sequentially as elements of an interacting network, filter water collected throughout their watersheds, and form a mosaic of predictable patterns. Traditional approaches to fisheries management such as stocking, regulating harvest, and in-lake habitat management do not always produce desired effects in reservoirs. As a result, managers may expend resources with little benefit to either fish or fishing. Some locally

  5. Heat Extraction Project, geothermal reservoir engineering research at Stanford

    Energy Technology Data Exchange (ETDEWEB)

    Kruger, P.

    1989-01-01

    The main objective of the SGP Heat Extraction Project is to provide a means for estimating the thermal behavior of geothermal fluids produced from fractured hydrothermal resources. The methods are based on estimated thermal properties of the reservoir components, reservoir management planning of production and reinjection, and the mixing of reservoir fluids: geothermal, resource fluid cooled by drawdown and infiltrating groundwater, and reinjected recharge heated by sweep flow through the reservoir formation. Several reports and publications, listed in Appendix A, describe the development of the analytical methods which were part of five Engineer and PhD dissertations, and the results from many applications of the methods to achieve the project objectives. The Heat Extraction Project is to evaluate the thermal properties of fractured geothermal resource and forecasted effects of reinjection recharge into operating reservoirs.

  6. Intermittent reservoir daily-inflow prediction using lumped and ...

    Indian Academy of Sciences (India)

    In this study, multi-linear regression (MLR) approach is used to construct intermittent reservoir daily inflow forecasting system. To illustrate the applicability and effect of using lumped and distributed input data in MLR approach, Koyna river watershed in Maharashtra, India is chosen as a case study. The results are also ...

  7. Gas deliverability forecasting - why bother?

    International Nuclear Information System (INIS)

    Trick, M.

    1996-01-01

    According to the author the answer to the question is an unequivocal 'yes' because gas production forecasting is extremely useful for the management and development of a gas field. To model a gas field, one must take into account reservoir performance, sandface inflow performance, wellbore pressure losses, gathering system pressure losses, and field facility performance. The integration of all these factors in a single computer-based model that incorporates proven technology will facilitate the evaluation of various development strategies. A good computer model can help to predict the most cost effective improvement methods, determine economic viability, estimate how much gas is available, evaluate whether drilling wells or adding compression will produce the most reserves, determine optimum placement of compression, evaluate changes to the gathering system, and determine if production from existing wells can be increased by wellbore modifications

  8. Inaccuracy in traffic forecasts

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent; Holm, Mette K. Skamris; Buhl, Søren Ladegaard

    2006-01-01

    that forecasters generally do a poor job of estimating the demand for transportation infrastructure projects. The result is substantial downside financial and economic risk. Forecasts have not become more accurate over the 30-year period studied. If techniques and skills for arriving at accurate demand forecasts...... forecasting. Highly inaccurate traffic forecasts combined with large standard deviations translate into large financial and economic risks. But such risks are typically ignored or downplayed by planners and decision-makers, to the detriment of social and economic welfare. The paper presents the data...

  9. Electricity demand forecasting techniques

    International Nuclear Information System (INIS)

    Gnanalingam, K.

    1994-01-01

    Electricity demand forecasting plays an important role in power generation. The two areas of data that have to be forecasted in a power system are peak demand which determines the capacity (MW) of the plant required and annual energy demand (GWH). Methods used in electricity demand forecasting include time trend analysis and econometric methods. In forecasting, identification of manpower demand, identification of key planning factors, decision on planning horizon, differentiation between prediction and projection (i.e. development of different scenarios) and choosing from different forecasting techniques are important

  10. Destratification of an impounding reservoir using compressed air??case of Mudi reservoir, Blantyre, Malawi

    Science.gov (United States)

    Chipofya, V. H.; Matapa, E. J.

    This paper reviews the operational and cost effectiveness of a compressed air destratification system that was installed in the Mudi reservoir for destratifying the reservoir. Mudi reservoir is a raw water source for the Blantyre Water Board. It has a capacity of 1,400,000 cubic metres. The reservoir is 15.3 m deep at top water level. In the absence of any artificial circulation of air, the reservoir stratifies into two layers. There is a warm epilimnion in the top 3 m of the reservoir, with temperatures ranging from 23 to 26 °C. There is prolific algal growth in this layer. The bottom layer has much lower temperatures, and is oxygen deficient. Under such anaerobic conditions, ammonia, sulphides, iron and manganese are released from the sediments of the reservoir. As a result of nutrient inflow from the catchments, coupled with tropical ambient temperatures, the reservoir is most times infested with blue-green algae. This results into water treatment problems in respect of taste and odour and iron and manganese soluble salts. To abate such problems, air is artificially circulated in the reservoir, near the intake tower, through a perforated pipe that is connected to an electrically driven compressor. This causes artificial circulation of water in the hypolimnion region of the reservoir. As a result of this circulation, a hostile environment that inhibits the propagation of algae is created. Dissolved oxygen and temperature profiles are practically uniform from top to bottom of reservoir. Concentrations of iron and manganese soluble salts are much reduced at any of the draw-off points available for the water treatment process. The paper concludes by highlighting the significant cost savings in water treatment that are accrued from the use of compressed air destratification in impounding water storage reservoirs for the control of algae and other chemical pollutants.

  11. Mrica Reservoir Sedimentation: Current Situation and Future Necessary Management

    Directory of Open Access Journals (Sweden)

    Puji Utomo

    2017-09-01

    Full Text Available Mrica Reservoir is one of many reservoirs located in Central Java that experienced a considerably high sedimentation during the last ten years. This condition has caused a rapid decrease in reservoir capacity. Various countermeasures have been introduced to reduce the rate of the reservoir sedimentation through catchment management and reservoir operation by means of flushing and/or dredging. However, the sedimentation remains intensive so that the fulfillment of water demand for electrical power generation was seriously affected. This paper presents the results of evaluation on the dynamics of the purpose of this research is to evaluate the sediment balance of the Mrica Reservoir based on two different scenarios, i.e. the existing condition and another certain type of reservoir management. The study on sediment balance was carried out by estimating the sediment inflow applying sheet erosion method in combination with the analysis of sediment rating curve. The measurement of the deposited sediment rate in the reservoir was conducted through the periodic echo sounding, whereas identification of the number of sediment that has been released from the reservoir was carried out through the observation on both flushing and dredging activities. The results show that during the last decade, the rate of the sediment inflow was approximately 5.869 MCM/year, whereas the released sediment from the reservoir was 4.097 MCM/year. In order to maintain the reservoir capacity, therefore, at least 1.772 MCM/year should be released from the reservoir by means of either flushing or dredging. Sedimentation management may prolong the reservoir’s service life to exceed the design life. Without sediment management, the lifetime of the reservoir would have finished by 2016, whereas with the proper management the lifetime may be extended to 2025.

  12. Design and development of bio-inspired framework for reservoir operation optimization

    Science.gov (United States)

    Asvini, M. Sakthi; Amudha, T.

    2017-12-01

    Frameworks for optimal reservoir operation play an important role in the management of water resources and delivery of economic benefits. Effective utilization and conservation of water from reservoirs helps to manage water deficit periods. The main challenge in reservoir optimization is to design operating rules that can be used to inform real-time decisions on reservoir release. We develop a bio-inspired framework for the optimization of reservoir release to satisfy the diverse needs of various stakeholders. In this work, single-objective optimization and multiobjective optimization problems are formulated using an algorithm known as "strawberry optimization" and tested with actual reservoir data. Results indicate that well planned reservoir operations lead to efficient deployment of the reservoir water with the help of optimal release patterns.

  13. Stream, Lake, and Reservoir Management.

    Science.gov (United States)

    Dai, Jingjing; Mei, Ying; Chang, Chein-Chi

    2017-10-01

    This review on stream, lake, and reservoir management covers selected 2016 publications on the focus of the following sections: Stream, lake, and reservoir management • Water quality of stream, lake, and reservoirReservoir operations • Models of stream, lake, and reservoir • Remediation and restoration of stream, lake, and reservoir • Biota of stream, lake, and reservoir • Climate effect of stream, lake, and reservoir.

  14. The Role of Rainfall Variability in Reservoir Storage Management at ...

    African Journals Online (AJOL)

    Bheema

    The objective is to develop functional hydrological relationship between (rainfall, inflow, reservoir storage and turbine releases) over the dam. This will provide scientific basis for operational decisions which can lead to optimum power plant utilization. 1.1. The Study Area. The study area is the Shiroro dam reservoir.

  15. Status of Wheeler Reservoir

    Energy Technology Data Exchange (ETDEWEB)

    1990-09-01

    This is one in a series of status reports prepared by the Tennessee Valley Authority (TVA) for those interested in the conditions of TVA reservoirs. This overview of Wheeler Reservoir summarizes reservoir purposes and operation, reservoir and watershed characteristics, reservoir uses and use impairments, and water quality and aquatic biological conditions. The information presented here is from the most recent reports, publications, and original data available. If no recent data were available, historical data were summarized. If data were completely lacking, environmental professionals with special knowledge of the resource were interviewed. 12 refs., 2 figs.

  16. Forecasting world natural gas supply

    International Nuclear Information System (INIS)

    Al-Fattah, S. M.; Startzman, R. A.

    2000-01-01

    Using the multi-cyclic Hubert approach, a 53 country-specific gas supply model was developed which enables production forecasts for virtually all of the world's gas. Supply models for some organizations such as OPEC, non-OPEC and OECD were also developed and analyzed. Results of the modeling study indicate that the world's supply of natural gas will peak in 2014, followed by an annual decline at the rate of one per cent per year. North American gas production is reported to be currently at its peak with 29 Tcf/yr; Western Europe will reach its peak supply in 2002 with 12 Tcf. According to this forecast the main sources of natural gas supply in the future will be the countries of the former Soviet Union and the Middle East. Between them, they possess about 62 per cent of the world's ultimate recoverable natural gas (4,880 Tcf). It should be noted that these estimates do not include unconventional gas resulting from tight gas reservoirs, coalbed methane, gas shales and gas hydrates. These unconventional sources will undoubtedly play an important role in the gas supply in countries such as the United States and Canada. 18 refs., 2 tabs., 18 figs

  17. ENSEMBLE methods to reconcile disparate national long range dispersion forecasts

    DEFF Research Database (Denmark)

    Mikkelsen, Torben; Galmarini, S.; Bianconi, R.

    2003-01-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparatenational forecasts for long-range dispersion....... ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidentalatmospheric release of radioactive material. A series of new decision-making “ENSEMBLE” procedures...

  18. A framework for improving a seasonal hydrological forecasting system using sensitivity analysis

    Science.gov (United States)

    Arnal, Louise; Pappenberger, Florian; Smith, Paul; Cloke, Hannah

    2017-04-01

    Seasonal streamflow forecasts are of great value for the socio-economic sector, for applications such as navigation, flood and drought mitigation and reservoir management for hydropower generation and water allocation to agriculture and drinking water. However, as we speak, the performance of dynamical seasonal hydrological forecasting systems (systems based on running seasonal meteorological forecasts through a hydrological model to produce seasonal hydrological forecasts) is still limited in space and time. In this context, the ESP (Ensemble Streamflow Prediction) remains an attractive forecasting method for seasonal streamflow forecasting as it relies on forcing a hydrological model (starting from the latest observed or simulated initial hydrological conditions) with historical meteorological observations. This makes it cheaper to run than a standard dynamical seasonal hydrological forecasting system, for which the seasonal meteorological forecasts will first have to be produced, while still producing skilful forecasts. There is thus the need to focus resources and time towards improvements in dynamical seasonal hydrological forecasting systems which will eventually lead to significant improvements in the skill of the streamflow forecasts generated. Sensitivity analyses are a powerful tool that can be used to disentangle the relative contributions of the two main sources of errors in seasonal streamflow forecasts, namely the initial hydrological conditions (IHC; e.g., soil moisture, snow cover, initial streamflow, among others) and the meteorological forcing (MF; i.e., seasonal meteorological forecasts of precipitation and temperature, input to the hydrological model). Sensitivity analyses are however most useful if they inform and change current operational practices. To this end, we propose a method to improve the design of a seasonal hydrological forecasting system. This method is based on sensitivity analyses, informing the forecasters as to which element of

  19. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Ruelke

    2013-01-01

    We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-)herding of forecasters. Forecasts are consistent with herding (anti-herding) of forecasters if forecasts are biased towards (away from...

  20. Stochastic Management of the Open Large Water Reservoir with Storage Function with Using a Genetic Algorithm

    Science.gov (United States)

    Kozel, Tomas; Stary, Milos

    2016-10-01

    Described models are used random forecasting period of flow line with different length. The length is shorter than 1 year. Forecasting period of flow line is transformed to line of managing discharges with same length as forecast. Adaptive managing is used only first value of line of discharges. Stochastic management is worked with dispersion of controlling discharge value. Main advantage stochastic management is fun of possibilities. In article is described construction and evaluation of adaptive stochastic model base on genetic algorithm (classic optimization method). Model was used for stochastic management of open large water reservoir with storage function. Genetic algorithm is used as optimization algorithm. Forecasted inflow is given to model and controlling discharge value is computed by model for chosen probability of controlling discharge value. Model was tested and validated on made up large open water reservoir. Results of stochastic model were evaluated for given probability and were compared to results of same model for 100% forecast (forecasted values are real values). The management of the large open water reservoir with storage function was done logically and with increased sum number of forecast from 300 to 500 the results given by model were better, but another increased from 500 to 750 and 1000 did not get expected improvement. Influence on course of management was tested for different length forecasted inflow and their sum number. Classical optimization model is needed too much time for calculation, therefore stochastic model base on genetic algorithm was used parallel calculation on cluster.

  1. Forecasting in Planning

    OpenAIRE

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively. Quantitative forecasting is illustrated with a brief overview of time series methods. Both qualitative and quantitative methods are illustrated by an example. The role and relative importance of forec...

  2. Commuter Airline Forecasts,

    Science.gov (United States)

    1981-05-01

    conterminous United States (48 contiguous states and the District of Columbia), for the State of Hawaii, and for the U.S. Carribean areas, Puerto Rico and U.S...FAA 15. Supplementary Notes I Abstract This publication presents forecasts of cammuter air carrier activity and describes the models designed for...forecasting Contenninous United States, Puerto Rico and the Virgin Islands, Hawaii, and individual airport activity. These forecasts take into account the

  3. Evaluation of model-based seasonal streamflow and water allocation forecasts for the Elqui Valley, Chile

    Science.gov (United States)

    Delorit, Justin; Cristian Gonzalez Ortuya, Edmundo; Block, Paul

    2017-09-01

    In many semi-arid regions, multisectoral demands often stress available water supplies. Such is the case in the Elqui River valley of northern Chile, which draws on a limited-capacity reservoir to allocate 25 000 water rights. Delayed infrastructure investment forces water managers to address demand-based allocation strategies, particularly in dry years, which are realized through reductions in the volume associated with each water right. Skillful season-ahead streamflow forecasts have the potential to inform managers with an indication of future conditions to guide reservoir allocations. This work evaluates season-ahead statistical prediction models of October-January (growing season) streamflow at multiple lead times associated with manager and user decision points, and links predictions with a reservoir allocation tool. Skillful results (streamflow forecasts outperform climatology) are produced for short lead times (1 September: ranked probability skill score (RPSS) of 0.31, categorical hit skill score of 61 %). At longer lead times, climatological skill exceeds forecast skill due to fewer observations of precipitation. However, coupling the 1 September statistical forecast model with a sea surface temperature phase and strength statistical model allows for equally skillful categorical streamflow forecasts to be produced for a 1 May lead, triggered for 60 % of years (1950-2015), suggesting forecasts need not be strictly deterministic to be useful for water rights holders. An early (1 May) categorical indication of expected conditions is reinforced with a deterministic forecast (1 September) as more observations of local variables become available. The reservoir allocation model is skillful at the 1 September lead (categorical hit skill score of 53 %); skill improves to 79 % when categorical allocation prediction certainty exceeds 80 %. This result implies that allocation efficiency may improve when forecasts are integrated into reservoir decision frameworks. The

  4. Induced seismicity in geothermal reservoirs: A review of forecasting approaches

    NARCIS (Netherlands)

    Gaucher, E.; Schoenball, M.; Heidbach, O.; Zang, A.; Fokker, P.A.; Wees, J.D. van; Kohl, T.

    2015-01-01

    In order to reach Europes 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced

  5. Induced seismicity in geothermal reservoirs : A review of forecasting approaches

    NARCIS (Netherlands)

    Gaucher, Emmanuel; Schoenball, Martin; Heidbach, Oliver; Zang, Arno; Fokker, Peter A.; Van Wees, Jan Diederik; Kohl, Thomas

    2015-01-01

    In order to reach Europes 2020 and 2050 targets in terms of greenhouse gas emissions, geothermal resources will have to contribute substantially to meeting carbon-free energy needs. However, public opinion may prevent future large-scale application of deep geothermal power plants, because induced

  6. Monthly reservoir inflow forecasting using a new hybrid SARIMA ...

    Indian Academy of Sciences (India)

    0.89, MAPE=43.4, CRM=0.053) outperforms SARIMA and GEP and SARIMA– ANN (R2=68.3, VAF=66.4, RMSE=1.12, MAPE=56.6, CRM=0.032) displays better performance than the SARIMA and ANN models. A comparison of the two hybrid ...

  7. Monthly reservoir inflow forecasting using a new hybrid SARIMA ...

    Indian Academy of Sciences (India)

    SARIMA models are linear and do not consider the random component of statistical data. To overcome this ... lake levels using artificial intelligence models and found that, compared with other models such as. ANN, GEP has .... that should be evaluated before modelling, and if they exist, they should be removed. The com-.

  8. Flood risk management for large reservoirs

    International Nuclear Information System (INIS)

    Poupart, M.

    2006-01-01

    Floods are a major risk for dams: uncontrolled reservoir water level may cause dam overtopping, and then its failure, particularly for fill dams. Poor control of spillway discharges must be taken into consideration too, as it can increase the flood consequences downstream. In both cases, consequences on the public or on properties may be significant. Spillway design to withstand extreme floods is one response to these risks, but must be complemented by strict operating rules: hydrological forecasting, surveillance and periodic equipment controls, operating guides and the training of operators are mandatory too, in order to guarantee safe operations. (author)

  9. Hydrodynamics and Water Quality forecasting over a Cloud Computing environment: INDIGO-DataCloud

    Science.gov (United States)

    Aguilar Gómez, Fernando; de Lucas, Jesús Marco; García, Daniel; Monteoliva, Agustín

    2017-04-01

    Algae Bloom due to eutrophication is an extended problem for water reservoirs and lakes that impacts directly in water quality. It can create a dead zone that lacks enough oxygen to support life and it can also be human harmful, so it must be controlled in water masses for supplying, bathing or other uses. Hydrodynamic and Water Quality modelling can contribute to forecast the status of the water system in order to alert authorities before an algae bloom event occurs. It can be used to predict scenarios and find solutions to reduce the harmful impact of the blooms. High resolution models need to process a big amount of data using a robust enough computing infrastructure. INDIGO-DataCloud (https://www.indigo-datacloud.eu/) is an European Commission funded project that aims at developing a data and computing platform targeting scientific communities, deployable on multiple hardware and provisioned over hybrid (private or public) e-infrastructures. The project addresses the development of solutions for different Case Studies using different Cloud-based alternatives. In the first INDIGO software release, a set of components are ready to manage the deployment of services to perform N number of Delft3D simulations (for calibrating or scenario definition) over a Cloud Computing environment, using the Docker technology: TOSCA requirement description, Docker repository, Orchestrator, AAI (Authorization, Authentication) and OneData (Distributed Storage System). Moreover, the Future Gateway portal based on Liferay, provides an user-friendly interface where the user can configure the simulations. Due to the data approach of INDIGO, the developed solutions can contribute to manage the full data life cycle of a project, thanks to different tools to manage datasets or even metadata. Furthermore, the cloud environment contributes to provide a dynamic, scalable and easy-to-use framework for non-IT experts users. This framework is potentially capable to automatize the processing of

  10. a Stochastic Approach to Multiobjective Optimization of Large-Scale Water Reservoir Networks

    Science.gov (United States)

    Bottacin-Busolin, A.; Worman, A. L.

    2013-12-01

    A main challenge for the planning and management of water resources is the development of multiobjective strategies for operation of large-scale water reservoir networks. The optimal sequence of water releases from multiple reservoirs depends on the stochastic variability of correlated hydrologic inflows and on various processes that affect water demand and energy prices. Although several methods have been suggested, large-scale optimization problems arising in water resources management are still plagued by the high dimensional state space and by the stochastic nature of the hydrologic inflows. In this work, the optimization of reservoir operation is approached using approximate dynamic programming (ADP) with policy iteration and function approximators. The method is based on an off-line learning process in which operating policies are evaluated for a number of stochastic inflow scenarios, and the resulting value functions are used to design new, improved policies until convergence is attained. A case study is presented of a multi-reservoir system in the Dalälven River, Sweden, which includes 13 interconnected reservoirs and 36 power stations. Depending on the late spring and summer peak discharges, the lowlands adjacent to Dalälven can often be flooded during the summer period, and the presence of stagnating floodwater during the hottest months of the year is the cause of a large proliferation of mosquitos, which is a major problem for the people living in the surroundings. Chemical pesticides are currently being used as a preventive countermeasure, which do not provide an effective solution to the problem and have adverse environmental impacts. In this study, ADP was used to analyze the feasibility of alternative operating policies for reducing the flood risk at a reasonable economic cost for the hydropower companies. To this end, mid-term operating policies were derived by combining flood risk reduction with hydropower production objectives. The performance

  11. House Price Forecasts, Forecaster Herding, and the Recent Crisis

    Directory of Open Access Journals (Sweden)

    Christian Pierdzioch

    2012-11-01

    Full Text Available We used the Wall Street Journal survey data for the period 2006–2012 to analyze whether forecasts of house prices and housing starts provide evidence of (anti-herding of forecasters. Forecasts are consistent with herding (anti-herding of forecasters if forecasts are biased towards (away from the consensus forecast. We found that anti-herding is prevalent among forecasters of house prices. We also report that, following the recent crisis, the prevalence of forecaster anti-herding seems to have changed over time.

  12. World Area Forecast System (WAFS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The World Area Forecast System (WAFS) is a worldwide system by which world area forecast centers provide aeronautical meteorological en-route forecasts in uniform...

  13. Modelling of Reservoir Operations using Fuzzy Logic and ANNs

    Science.gov (United States)

    Van De Giesen, N.; Coerver, B.; Rutten, M.

    2015-12-01

    Today, almost 40.000 large reservoirs, containing approximately 6.000 km3 of water and inundating an area of almost 400.000 km2, can be found on earth. Since these reservoirs have a storage capacity of almost one-sixth of the global annual river discharge they have a large impact on the timing, volume and peaks of river discharges. Global Hydrological Models (GHM) are thus significantly influenced by these anthropogenic changes in river flows. We developed a parametrically parsimonious method to extract operational rules based on historical reservoir storage and inflow time-series. Managing a reservoir is an imprecise and vague undertaking. Operators always face uncertainties about inflows, evaporation, seepage losses and various water demands to be met. They often base their decisions on experience and on available information, like reservoir storage and the previous periods inflow. We modeled this decision-making process through a combination of fuzzy logic and artificial neural networks in an Adaptive-Network-based Fuzzy Inference System (ANFIS). In a sensitivity analysis, we compared results for reservoirs in Vietnam, Central Asia and the USA. ANFIS can indeed capture reservoirs operations adequately when fed with a historical monthly time-series of inflows and storage. It was shown that using ANFIS, operational rules of existing reservoirs can be derived without much prior knowledge about the reservoirs. Their validity was tested by comparing actual and simulated releases with each other. For the eleven reservoirs modelled, the normalised outflow, , was predicted with a MSE of 0.002 to 0.044. The rules can be incorporated into GHMs. After a network for a specific reservoir has been trained, the inflow calculated by the hydrological model can be combined with the release and initial storage to calculate the storage for the next time-step using a mass balance. Subsequently, the release can be predicted one time-step ahead using the inflow and storage.

  14. Forecasting in Planning

    NARCIS (Netherlands)

    Ike, P.; Voogd, Henk; Voogd, Henk; Linden, Gerard

    2004-01-01

    This chapter begins with a discussion of qualitative forecasting by describing a number of methods that depend on judgements made by stakeholders, experts or other interested parties to arrive at forecasts. Two qualitative approaches are illuminated, the Delphi and scenario methods respectively.

  15. Reservoir engineering studies of the Cerro Prieto geothermal field

    Science.gov (United States)

    Goyal, K. P.; Lippmann, M. J.; Tsang, C. F.

    1982-09-01

    Reservoir engineering studies of the Cerro Prieto geothermal field began in 1978 under a five-year cooperative agreement between the US Department of Energy and the Comision Federal de Electricidad de Mexico, with the ultimate objective of simulating the reservoir to forecast its production capacity, energy longevity, and recharge capability under various production and injection scenarios. During the fiscal year 1981, attempts were made to collect information on the evolution history of the field since exploitation began; the information is to be used later to validate the reservoir model. To this end, wellhead production data were analyzed for heat and mass flow and also for changes in reservoir pressures, temperatures, and saturations for the period from March 1973 to November 1980.

  16. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Jun-He Yang

    2017-01-01

    Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  17. Transport of reservoir fines

    DEFF Research Database (Denmark)

    Yuan, Hao; Shapiro, Alexander; Stenby, Erling Halfdan

    Modeling transport of reservoir fines is of great importance for evaluating the damage of production wells and infectivity decline. The conventional methodology accounts for neither the formation heterogeneity around the wells nor the reservoir fines’ heterogeneity. We have developed an integral...

  18. SILTATION IN RESERVOIRS

    African Journals Online (AJOL)

    Calls have been made to the government through various media to assist its populace in combating this nagging problem. It was concluded that sediment maximum accumulation is experienced in reservoir during the periods of maximum flow. Keywords: reservoir model, siltation, sediment, catchment, sediment transport. 1.

  19. Dynamic reservoir well interaction

    NARCIS (Netherlands)

    Sturm, W.L.; Belfroid, S.P.C.; Wolfswinkel, O. van; Peters, M.C.A.M.; Verhelst, F.J.P.C.M.

    2004-01-01

    In order to develop smart well control systems for unstable oil wells, realistic modeling of the dynamics of the well is essential. Most dynamic well models use a semi-steady state inflow model to describe the inflow of oil and gas from the reservoir. On the other hand, reservoir models use steady

  20. Reservoir Engineering Management Program

    Energy Technology Data Exchange (ETDEWEB)

    Howard, J.H.; Schwarz, W.J.

    1977-12-14

    The Reservoir Engineering Management Program being conducted at Lawrence Berkeley Laboratory includes two major tasks: 1) the continuation of support to geothermal reservoir engineering related work, started under the NSF-RANN program and transferred to ERDA at the time of its formation; 2) the development and subsequent implementation of a broad plan for support of research in topics related to the exploitation of geothermal reservoirs. This plan is now known as the GREMP plan. Both the NSF-RANN legacies and GREMP are in direct support of the DOE/DGE mission in general and the goals of the Resource and Technology/Resource Exploitation and Assessment Branch in particular. These goals are to determine the magnitude and distribution of geothermal resources and reduce risk in their exploitation through improved understanding of generically different reservoir types. These goals are to be accomplished by: 1) the creation of a large data base about geothermal reservoirs, 2) improved tools and methods for gathering data on geothermal reservoirs, and 3) modeling of reservoirs and utilization options. The NSF legacies are more research and training oriented, and the GREMP is geared primarily to the practical development of the geothermal reservoirs. 2 tabs., 3 figs.

  1. A snow and ice melt seasonal prediction modelling system for Alpine reservoirs

    Science.gov (United States)

    Förster, Kristian; Oesterle, Felix; Hanzer, Florian; Schöber, Johannes; Huttenlau, Matthias; Strasser, Ulrich

    2016-10-01

    The timing and the volume of snow and ice melt in Alpine catchments are crucial for management operations of reservoirs and hydropower generation. Moreover, a sustainable reservoir operation through reservoir storage and flow control as part of flood risk management is important for downstream communities. Forecast systems typically provide predictions for a few days in advance. Reservoir operators would benefit if lead times could be extended in order to optimise the reservoir management. Current seasonal prediction products such as the NCEP (National Centers for Environmental Prediction) Climate Forecast System version 2 (CFSv2) enable seasonal forecasts up to nine months in advance, with of course decreasing accuracy as lead-time increases. We present a coupled seasonal prediction modelling system that runs at monthly time steps for a small catchment in the Austrian Alps (Gepatschalm). Meteorological forecasts are obtained from the CFSv2 model. Subsequently, these data are downscaled to the Alpine Water balance And Runoff Estimation model AWARE running at monthly time step. Initial conditions are obtained using the physically based, hydro-climatological snow model AMUNDSEN that predicts hourly fields of snow water equivalent and snowmelt at a regular grid with 50 m spacing. Reservoir inflow is calculated taking into account various runs of the CFSv2 model. These simulations are compared with observed inflow volumes for the melting and accumulation period 2015.

  2. Simulation of Reservoir Sediment Flushing of the Three Gorges Reservoir Using an Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Xueying Li

    2016-05-01

    Full Text Available Reservoir sedimentation and its effect on the environment are the most serious world-wide problems in water resources development and utilization today. As one of the largest water conservancy projects, the Three Gorges Reservoir (TGR has been controversial since its demonstration period, and sedimentation is the major concern. Due to the complex physical mechanisms of water and sediment transport, this study adopts the Error Back Propagation Training Artificial Neural Network (BP-ANN to analyze the relationship between the sediment flushing efficiency of the TGR and its influencing factors. The factors are determined by the analysis on 1D unsteady flow and sediment mathematical model, mainly including reservoir inflow, incoming sediment concentration, reservoir water level, and reservoir release. Considering the distinguishing features of reservoir sediment delivery in different seasons, the monthly average data from 2003, when the TGR was put into operation, to 2011 are used to train, validate, and test the BP-ANN model. The results indicate that, although the sample space is quite limited, the whole sediment delivery process can be schematized by the established BP-ANN model, which can be used to help sediment flushing and thus decrease the reservoir sedimentation.

  3. Restoring Natural Streamflow Variability by Modifying Multi-purpose Reservoir Operation

    Science.gov (United States)

    Shiau, J.

    2010-12-01

    Multi-purpose reservoirs typically provide benefits of water supply, hydroelectric power, and flood mitigation. Hydroelectric power generations generally do not consume water. However, temporal distribution of downstream flows is highly changed due to hydro-peaking effects. Associated with offstream diversion of water supplies for municipal, industrial, and agricultural requirements, natural streamflow characteristics of magnitude, duration, frequency, timing, and rate of change is significantly altered by multi-purpose reservoir operation. Natural flow regime has long been recognized a master factor for ecosystem health and biodiversity. Restoration of altered flow regime caused by multi-purpose reservoir operation is the main objective of this study. This study presents an optimization framework that modifying reservoir operation to seeking balance between human and environmental needs. The methodology presented in this study is applied to the Feitsui Reservoir, located in northern Taiwan, with main purpose of providing stable water-supply and auxiliary purpose of electricity generation and flood-peak attenuation. Reservoir releases are dominated by two decision variables, i.e., duration of water releases for each day and percentage of daily required releases within the duration. The current releasing policy of the Feitsui Reservoir releases water for water-supply and hydropower purposes during 8:00 am to 16:00 pm each day and no environmental flows releases. Although greater power generation is obtained by 100% releases distributed within 8-hour period, severe temporal alteration of streamflow is observed downstream of the reservoir. Modifying reservoir operation by relaxing these two variables and reserve certain ratio of streamflow as environmental flow to maintain downstream natural variability. The optimal reservoir releasing policy is searched by the multi-criterion decision making technique for considering reservoir performance in terms of shortage ratio

  4. The strategy of professional forecasting

    DEFF Research Database (Denmark)

    Ottaviani, Marco; Sørensen, Peter Norman

    2006-01-01

    We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts and the ......We develop and compare two theories of professional forecasters’ strategic behavior. The first theory, reputational cheap talk, posits that forecasters endeavor to convince the market that they are well informed. The market evaluates their forecasting talent on the basis of the forecasts...... and the realized state. If the market expects forecasters to report their posterior expectations honestly, then forecasts are shaded toward the prior mean. With correct market expectations, equilibrium forecasts are imprecise but not shaded. The second theory posits that forecasters compete in a forecasting...

  5. Climate variability and sedimentation of a hydropower reservoir

    International Nuclear Information System (INIS)

    Riedel, M.

    2008-01-01

    This presentation discussed a large-scale watershed and reservoir sedimentation model developed to predict potential sedimentation scenarios for a large hydroelectric power project located in the central Appalachians. The geographic information system (GIS) watershed model was calibrated using observed long-term meteorological and hydrological data. Potential development scenarios were then used to construct future watershed land cover scenarios. Future climate change regimes and precipitation and temperature pattern shifts were identified using climatic variability and potential change analyses. Results of the study were then forecast for a period of 50 years and used to develop sediment yield regimes for the project's reservoir. The model was validated using reservoir and fields studies for watershed, river, and reservoir hydrodynamics. The resulting 3-D hydrological sedimentation model was then used to forecast changes in river sedimentation and storage capacity under various future climate scenarios. Results of the study showed the development of unique zones of advancing sediment deltas and temporary storage areas. Warmer and wetter scenarios produced sedimentation impacts similar to scenarios without climatic change. It was concluded that results of the analyses will be used to help reduce future soil losses in the reservoir. tabs., figs

  6. Spatial electric load forecasting

    CERN Document Server

    Willis, H Lee

    2002-01-01

    Spatial Electric Load Forecasting Consumer Demand for Power and ReliabilityCoincidence and Load BehaviorLoad Curve and End-Use ModelingWeather and Electric LoadWeather Design Criteria and Forecast NormalizationSpatial Load Growth BehaviorSpatial Forecast Accuracy and Error MeasuresTrending MethodsSimulation Method: Basic ConceptsA Detailed Look at the Simulation MethodBasics of Computerized SimulationAnalytical Building Blocks for Spatial SimulationAdvanced Elements of Computerized SimulationHybrid Trending-Simulation MethodsAdvanced

  7. [Research progress on phosphorus budgets and regulations in reservoirs].

    Science.gov (United States)

    Shen, Xiao; Li, Xu; Zhang, Wang-shou

    2014-12-01

    Phosphorus is an important limiting factor of water eutrophication. A clear understanding of its budget and regulated method is fundamental for reservoir ecological health. In order to pro- mote systematic research further and improve phosphorus regulation system, the budget balance of reservoir phosphorus and its influencing factors were concluded, as well as conventional regulation and control measures. In general, the main phosphorus sources of reservoirs include upstream input, overland runoff, industrial and domestic wastewater, aquaculture, atmospheric deposition and sediment release. Upstream input is the largest phosphorus source among them. The principal output path of phosphorus is the flood discharge, the emission load of which is mainly influenced by drainage patterns. In addition, biological harvest also can export a fraction of phosphorus. There are some factors affecting the reservoir phosphorus balance, including reservoirs' function, hydrological conditions, physical and chemical properties of water, etc. Therefore, the phosphorus budgets of different reservoirs vary greatly, according to different seasons and regions. In order to reduce the phosphorus loading in reservoirs, some methods are carried out, including constructed wetlands, prefix reservoir, sediment dredging, biomanipulation, etc. Different methods need to be chosen and combined according to different reservoirs' characteristics and water quality management goals. Thus, in the future research, it is reasonable to highlight reservoir ecological characteristics and proceed to a complete and systematic analysis of the inherent complexity of phosphorus budget and its impact factors for the reservoirs' management. Besides, the interaction between phosphorus budget and other nutrients in reservoirs also needs to be conducted. It is fundamental to reduce the reservoirs' phosphorus loading to establish a scientific and improved management system based on those researches.

  8. Z-M in lightning forecasting

    OpenAIRE

    Machina, Alexia J.

    2009-01-01

    Approved for public release, distribution unlimited Frozen hydrometeors are required for a storm to produce lightning. Previous research has made strong correlations between ice mass and lightning flash rate and lightning flash density. This study attempted to correlate ice mass to lightning potential Operational interest is centered at Cape Canaveral Air Force Station/Kennedy Space Center where accurate weather forecasting is vital to mission requirements, resource protection, and pe...

  9. Sediment management for reservoir

    International Nuclear Information System (INIS)

    Rahman, A.

    2005-01-01

    All natural lakes and reservoirs whether on rivers, tributaries or off channel storages are doomed to be sited up. Pakistan has two major reservoirs of Tarbela and Managla and shallow lake created by Chashma Barrage. Tarbela and Mangla Lakes are losing their capacities ever since first impounding, Tarbela since 1974 and Mangla since 1967. Tarbela Reservoir receives average annual flow of about 62 MAF and sediment deposits of 0.11 MAF whereas Mangla gets about 23 MAF of average annual flows and is losing its storage at the rate of average 34,000 MAF annually. The loss of storage is a great concern and studies for Tarbela were carried out by TAMS and Wallingford to sustain its capacity whereas no study has been done for Mangla as yet except as part of study for Raised Mangla, which is only desk work. Delta of Tarbala reservoir has advanced to about 6.59 miles (Pivot Point) from power intakes. In case of liquefaction of delta by tremor as low as 0.12g peak ground acceleration the power tunnels I, 2 and 3 will be blocked. Minimum Pool of reservoir is being raised so as to check the advance of delta. Mangla delta will follow the trend of Tarbela. Tarbela has vast amount of data as reservoir is surveyed every year, whereas Mangla Reservoir survey was done at five-year interval, which has now been proposed .to be reduced to three-year interval. In addition suspended sediment sampling of inflow streams is being done by Surface Water Hydrology Project of WAPDA as also some bed load sampling. The problem of Chasma Reservoir has also been highlighted, as it is being indiscriminately being filled up and drawdown several times a year without regard to its reaction to this treatment. The Sediment Management of these reservoirs is essential and the paper discusses pros and cons of various alternatives. (author)

  10. Forecasting Future Sea Ice Conditions: A Lagrangian Approach

    Science.gov (United States)

    2015-09-30

    Journal of Climate, in revision). The decadal forecasting of the minimum sea ice extent based on the output of 30 ensemble members of the Community...1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Forecasting Future Sea Ice Conditions: A Lagrangian...1- Show from observations whether the dynamics of the multi -year pack ice has a influence on the location of the following summer MIZ. 2

  11. NYHOPS Forecast Model Results

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 3D Marine Nowcast/Forecast System for the New York Bight NYHOPS subdomain. Currents, waves, surface meteorology, and water conditions.

  12. Mercury and methylmercury in reservoirs in Indiana

    Science.gov (United States)

    Risch, Martin R.; Fredericksen, Amanda L.

    2015-01-01

    Mercury (Hg) is an element that occurs naturally, but evidence suggests that human activities have resulted in increased amounts being released to the atmosphere and land surface. When Hg is converted to methylmercury (MeHg) in aquatic ecosystems, MeHg accumulates and increases in the food web so that some fish contain levels which pose a health risk to humans and wildlife that consume these fish. Reservoirs unlike natural lakes, are a part of river systems that are managed for flood control. Data compiled and interpreted for six flood-control reservoirs in Indiana showed a relation between Hg transport, MeHg formation in water, and MeHg in fish that was influenced by physical, chemical, and biological differences among the reservoirs. Existing information precludes a uniform comparison of Hg and MeHg in all reservoirs in the State, but factors and conditions were identified that can indicate where and when Hg and MeHg levels in reservoirs could be highest.

  13. Reservoir characterization of Pennsylvanian sandstone reservoirs. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Kelkar, M.

    1995-02-01

    This final report summarizes the progress during the three years of a project on Reservoir Characterization of Pennsylvanian Sandstone Reservoirs. The report is divided into three sections: (i) reservoir description; (ii) scale-up procedures; (iii) outcrop investigation. The first section describes the methods by which a reservoir can be described in three dimensions. The next step in reservoir description is to scale up reservoir properties for flow simulation. The second section addresses the issue of scale-up of reservoir properties once the spatial descriptions of properties are created. The last section describes the investigation of an outcrop.

  14. Constrained genetic algorithms for optimizing multi-use reservoir operation

    Science.gov (United States)

    Chang, Li-Chiu; Chang, Fi-John; Wang, Kuo-Wei; Dai, Shin-Yi

    2010-08-01

    To derive an optimal strategy for reservoir operations to assist the decision-making process, we propose a methodology that incorporates the constrained genetic algorithm (CGA) where the ecological base flow requirements are considered as constraints to water release of reservoir operation when optimizing the 10-day reservoir storage. Furthermore, a number of penalty functions designed for different types of constraints are integrated into reservoir operational objectives to form the fitness function. To validate the applicability of this proposed methodology for reservoir operations, the Shih-Men Reservoir and its downstream water demands are used as a case study. By implementing the proposed CGA in optimizing the operational performance of the Shih-Men Reservoir for the last 20 years, we find this method provides much better performance in terms of a small generalized shortage index (GSI) for human water demands and greater ecological base flows for most of the years than historical operations do. We demonstrate the CGA approach can significantly improve the efficiency and effectiveness of water supply capability to both human and ecological base flow requirements and thus optimize reservoir operations for multiple water users. The CGA can be a powerful tool in searching for the optimal strategy for multi-use reservoir operations in water resources management.

  15. Forecast communication through the newspaper Part 2: perceptions of uncertainty

    Science.gov (United States)

    Harris, Andrew J. L.

    2015-04-01

    In the first part of this review, I defined the media filter and how it can operate to frame and blame the forecaster for losses incurred during an environmental disaster. In this second part, I explore the meaning and role of uncertainty when a forecast, and its basis, is communicated through the response and decision-making chain to the newspaper, especially during a rapidly evolving natural disaster which has far-reaching business, political, and societal impacts. Within the media-based communication system, there remains a fundamental disconnect of the definition of uncertainty and the interpretation of the delivered forecast between various stakeholders. The definition and use of uncertainty differs especially between scientific, media, business, and political stakeholders. This is a serious problem for the scientific community when delivering forecasts to the public though the press. As reviewed in Part 1, the media filter can result in a negative frame, which itself is a result of bias, slant, spin, and agenda setting introduced during passage of the forecast and its uncertainty through the media filter. The result is invariably one of anger and fury, which causes loss of credibility and blaming of the forecaster. Generation of a negative frame can be aided by opacity of the decision-making process that the forecast is used to support. The impact of the forecast will be determined during passage through the decision-making chain where the precautionary principle and cost-benefit analysis, for example, will likely be applied. Choice of forecast delivery format, vehicle of communication, syntax of delivery, and lack of follow-up measures can further contribute to causing the forecast and its role to be misrepresented. Follow-up measures to negative frames may include appropriately worded press releases and conferences that target forecast misrepresentation or misinterpretation in an attempt to swing the slant back in favor of the forecaster. Review of

  16. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hitzman, D.O.; Stepp, A.K.; Dennis, D.M.; Graumann, L.R.

    2003-02-11

    This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents.

  17. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hitzman, D.O.; Bailey, S.A.; Stepp, A.K.

    2003-02-11

    This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil releasing agents. The potential of the system will be illustrated and demonstrated by the example of biopolymer production on oil recovery.

  18. Reservoirs on the mountain rivers and their safety

    Directory of Open Access Journals (Sweden)

    Ts.Z. Basilashvili

    2016-06-01

    Full Text Available Water resource issues and problems in the world's developing countries, present special challenges, as development of these countries significantly depends on the utilization of water resources. Georgia nestled between the Black Sea, Russia, and Turkey, and surrounded by the Caucasus Mountains, occupies a unique geographic space, which gives it strategic importance far beyond its size. Though blessed by its rich hydro resources, Georgia due to its uneven distribution, experiences some problems as the demand on water frequently doesn't coincide with water provision. As a result it causes acute deficit situation. Due to the global warming of the climate, it is expected that the fresh water amount will decrease in Georgia. This is why it is necessary to approach the use of water resources in a complex way by means of water reservoirs, which will enable attaining of a large economic effect. In the mountainous conditions filling of reservoirs take place in spring time, when snow and glaciers melt. In Georgia as in mountainous country, abundant rains take place, thus causing catastrophic flooding on rivers. In summer and winter water amount decreases 10 times and irrigation, water provision and energy production is impeded. Thus, the lack of water just like the excess amount of water causes damage. This is why it is needed to forecast water amount in water reservoirs for different periods of the year. But in a complex, mountainous terrain operative data of hydrometeorology is not sufficient for application of modern mathematical methods. We have elaborated multiple-factor statistical model for a forecast, which by means of different mathematical criteria and methods can simultaneously research the increase of the timeliness of forecasts and the level of their precision. We have obtained methodologies for short and long term forecasts of inflowing water properties in Georgia's main water reservoirs to further plan optimally and regulate water resources

  19. Appraisal of transport and deformation in shale reservoirs using natural noble gas tracers

    Energy Technology Data Exchange (ETDEWEB)

    Heath, Jason E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kuhlman, Kristopher L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Robinson, David G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bauer, Stephen J. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gardner, William Payton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of Montana, Missoula, MT (United States)

    2015-09-01

    This report presents efforts to develop the use of in situ naturally-occurring noble gas tracers to evaluate transport mechanisms and deformation in shale hydrocarbon reservoirs. Noble gases are promising as shale reservoir diagnostic tools due to their sensitivity of transport to: shale pore structure; phase partitioning between groundwater, liquid, and gaseous hydrocarbons; and deformation from hydraulic fracturing. Approximately 1.5-year time-series of wellhead fluid samples were collected from two hydraulically-fractured wells. The noble gas compositions and isotopes suggest a strong signature of atmospheric contribution to the noble gases that mix with deep, old reservoir fluids. Complex mixing and transport of fracturing fluid and reservoir fluids occurs during production. Real-time laboratory measurements were performed on triaxially-deforming shale samples to link deformation behavior, transport, and gas tracer signatures. Finally, we present improved methods for production forecasts that borrow statistical strength from production data of nearby wells to reduce uncertainty in the forecasts.

  20. Operational flood forecasting: further lessons learned form a recent inundation in Tuscany, Italy

    Science.gov (United States)

    Caparrini, F.; Castelli, F.; di Carlo, E.

    2010-09-01

    After a few years of experimental setup, model refinement and parameters calibration, a distributed flood forecasting system for the Tuscany region was promoted to operational use in early 2008. The hydrologic core of the system, MOBIDIC, is a fully distributed soil moisture accounting model, with sequential assimilation of hydrometric data. The model is forced by the real-time dense hydrometeorological network of the Regional Hydrologic Service as well from the QPF products of a number of different limited area meteorological models (LAMI, WRF+ECMWF, WRF+GFS). Given the relatively short response time of the Tuscany basins, the river flow forecasts based on ground measured precipitation are operationally used mainly as a monitoring tool, while the true usable predictions are necessarily based on the QPF input. The first severe flooding event the system had to face occurred in late December 2009, when a failure of the right levee of the Serchio river caused an extensive inundation (on December 25th). In the days following the levee breaking, intensive monitoring and forecast was needed (another flood peak occurred on the night between December 29th and January 1st 2010) as a support for decisions regarding the management of the increased vulnerability of the area and the planning of emergency reparation works at the river banks. The operational use of the system during such a complex event, when both the meteorological and the hydrological components may be said to have performed well form a strict modeling point of view, brought to attention a number of additional issues about the system as a whole. The main of these issues may be phrased in terms of additional system requirements, namely: the ranking of different QPF products in terms of some likelihood measure; the rapid redefinition of alarm thresholds due to sudden changes in the river flow capacity; the supervised prediction for evaluating the consequences of different management scenarios for reservoirs

  1. Study of the impact of the uncertainties in petroleum reservoir behavior; Estudo do impacto de incertezas no desempenho de reservatorios de petroleo

    Energy Technology Data Exchange (ETDEWEB)

    Loschiavo, Roberto [PETROBRAS S.A., SE/AL (Brazil). Exploracao e Producao]. E-mail: rloschiavo@ep-seal.petrobras.com.br; Schiozer, Denis J. [Universidade Estadual de Campinas, SP (Brazil). Centro de Estudo do Petroleo (CEPETRO)]. E-mail: denis@cepetro.unicamp.br; Steagall, Daniel Escobar [Universidade Estadual de Campinas, SP (Brazil). Faculdade de Engenharia Mecanica]. E-mail: steagall@dep.fem.unicamp.br

    2000-07-01

    Economic evaluation of a project as well as facilities design for oil exploitation is, in general, based on production forecasts. Since production forecast depends on several parameters that are not completely known, one should take a probabilistic approach for reservoir modeling and numerical flow simulation. With this research we propose a procedure to estimate probabilistic production forecasts profiles based on the decision tree technique. The most influencing parameters of a reservoir model are identified and combined to generate a number of realizations of the reservoirs. The combination of each branch of the decision tree defines the probability associated to each reservoir model. A computer program was developed to automatically generate the reservoir models, submit them to the numerical simulator, and process the results. Parallel computing was used to improve the performance of the procedure. (author)

  2. Methane emissions from northern Amazon savanna wetlands and Balbina Reservoir

    Science.gov (United States)

    Kemenes, A.; Belger, L.; Forsberg, B.; Melack, J. M.

    2006-12-01

    To improve estimates of methane emission for the Amazon basin requires information from aquatic environments not represented in the central basin near the Solimoes River, where most of the current data were obtained. We have combined intensive, year-long measurements of methane emission and water levels made in interfluvial wetlands located in the upper Negro basin with calculations of inundation based on a time series of Radarsat synthetic aperature radar images. These grass-dominated savannas emitted methane at an average rate of 18 mg C per m squared per day, a low rate compared to the habitats with floating grasses the occur in the Solimoes floodplains. Reservoirs constructed in the Amazon typically flood forested landscapes and lead to conditions conducive for methane production. The methane is released to the atmosphere from the reservoir and as the water exits the turbines and from the downstream river. Balbina Reservoir near Manaus covers about 2400 km squared along the Uatuma River. Annual averages of measurements of methane emission from the various habitats in the reservoir range from 23 to 64 mg C per m squared per day. Total annual emission from the reservoir is about 58 Gg C. In addition, about 39 Gg C per year are released below the dam, about 50 percent of which is released as the water passes through the turbines. On an annual areal basis, Balbina Reservoir emits 40 Mg C km squared, in contrast to 30 Mg km squared for the Solimoes mainstem floodplain

  3. Space Weather Forecasting at IZMIRAN

    Science.gov (United States)

    Gaidash, S. P.; Belov, A. V.; Abunina, M. A.; Abunin, A. A.

    2017-12-01

    Since 1998, the Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation (IZMIRAN) has had an operating heliogeophysical service—the Center for Space Weather Forecasts. This center transfers the results of basic research in solar-terrestrial physics into daily forecasting of various space weather parameters for various lead times. The forecasts are promptly available to interested consumers. This article describes the center and the main types of forecasts it provides: solar and geomagnetic activity, magnetospheric electron fluxes, and probabilities of proton increases. The challenges associated with the forecasting of effects of coronal mass ejections and coronal holes are discussed. Verification data are provided for the center's forecasts.

  4. Real-time optimisation of the Hoa Binh reservoir, Vietnam

    DEFF Research Database (Denmark)

    Richaud, Bertrand; Madsen, Henrik; Rosbjerg, Dan

    2011-01-01

    Multi-purpose reservoirs often have to be managed according to conflicting objectives, which requires efficient tools for trading-off the objectives. This paper proposes a multi-objective simulation-optimisation approach that couples off-line rule curve optimisation with on-line real......-time optimisation. First, the simulation-optimisation framework is applied for optimising reservoir operating rules. Secondly, real-time and forecast information is used for on-line optimisation that focuses on short-term goals, such as flood control or hydropower generation, without compromising the deviation...... of the long-term objectives from the optimised rule curves. The method is illustrated for optimisation of the Hoa Binh reservoir in Vietnam. The approach is proven efficient to trade-off conflicting objectives. Selected by a Pareto optimisation method, the preferred optimum is able to mitigate the floods...

  5. The HEPEX Seasonal Streamflow Forecast Intercomparison Project

    Science.gov (United States)

    Wood, A. W.; Schepen, A.; Bennett, J.; Mendoza, P. A.; Ramos, M. H.; Wetterhall, F.; Pechlivanidis, I.

    2016-12-01

    The Hydrologic Ensemble Prediction Experiment (HEPEX; www.hepex.org) has launched an international seasonal streamflow forecasting intercomparison project (SSFIP) with the goal of broadening community knowledge about the strengths and weaknesses of various operational approaches being developed around the world. While some of these approaches have existed for decades (e.g. Ensemble Streamflow Prediction - ESP - in the United States and elsewhere), recent years have seen the proliferation of new operational and experimental streamflow forecasting approaches. These have largely been developed independently in each country, thus it is difficult to assess whether the approaches employed in some centers offer more promise for development than others. This motivates us to establish a forecasting testbed to facilitate a diagnostic evaluation of a range of different streamflow forecasting approaches and their components over a common set of catchments, using a common set of validation methods. Rather than prescribing a set of scientific questions from the outset, we are letting the hindcast results and notable differences in methodologies on a watershed-specific basis motivate more targeted analyses and sub-experiments that may provide useful insights. The initial pilot of the testbed involved two approaches - CSIRO's Bayesian joint probability (BJP) and NCAR's sequential regression - for two catchments, each designated by one of the teams (the Murray River, Australia, and Hungry Horse reservoir drainage area, USA). Additional catchments/approaches are in the process of being added to the testbed. To support this CSIRO and NCAR have developed data and analysis tools, data standards and protocols to formalize the experiment. These include requirements for cross-validation, verification, reference climatologies, and common predictands. This presentation describes the SSFIP experiments, pilot basin results and scientific findings to date.

  6. Modeling Reservoir Formation Damage due to Water Injection for Oil Recovery

    DEFF Research Database (Denmark)

    Yuan, Hao

    2010-01-01

    The elliptic equation for non-Fickian transport of suspension in porous media is applied to simulate the reservoir formation damage due to water injection for oil recovery. The deposition release (erosion of reservoir formation) and the suspension deposition (pore plugging) are both taken...... into account. 1-D numerical simulations are carried out to reveal the erosion of reservoir formation due to water injection. 2-D numerical simulations are carried out to obtain the suspension and deposition profiles around the injection wells. These preliminary results indicate the non-Fickian behaviors...... of suspended reservoir fines and the corresponding formation damage due to erosion and relocation of reservoir fines....

  7. Financial Analysts’ Forecasts

    DEFF Research Database (Denmark)

    Stæhr, Simone

    in the decision making and the magnitude of these constraints does sometimes vary with personal traits. Therefore, to the extent that financial analysts are subjects to behavioral biases their outputs to the investors are likely to be biased by their interpretation of information. Because investors need accuracy....... The primary focus is on financial analysts in the task of conducting earnings forecasts while a secondary focus is on investors’ abilities to interpret and make use of these forecasts. Simply put, financial analysts can be seen as information intermediators receiving inputs to their analyses from firm...... management and providing outputs to the investors. Amongst various outputs from the analysts are forecasts of earnings. According to decision theories mostly from the literature in psychology all humans are affected by cognitive constraints to some degree. These constraints may lead to unintentional biases...

  8. Verification of Spatial Forecasts of Continuous Meteorological Variables Using Categorical and Object-Based Methods

    Science.gov (United States)

    2016-08-01

    or missions. This report presents methods to verify forecast fields of meteorological variables that have been filtered by the application of a...forecast-evaluation technique has great potential in assessing forecasts of continuous variables that have been filtered by the application of a threshold...Distribution List 30 Approved for public release; distribution is unlimited. iv List of Figures Fig. 1 Triple- nested model domains: domain center

  9. Streamflow Forecasting Using Nuero-Fuzzy Inference System

    Science.gov (United States)

    Nanduri, U. V.; Swain, P. C.

    2005-12-01

    The prediction of flow into a reservoir is fundamental in water resources planning and management. The need for timely and accurate streamflow forecasting is widely recognized and emphasized by many in water resources fraternity. Real-time forecasts of natural inflows to reservoirs are of particular interest for operation and scheduling. The physical system of the river basin that takes the rainfall as an input and produces the runoff is highly nonlinear, complicated and very difficult to fully comprehend. The system is influenced by large number of factors and variables. The large spatial extent of the systems forces the uncertainty into the hydrologic information. A variety of methods have been proposed for forecasting reservoir inflows including conceptual (physical) and empirical (statistical) models (WMO 1994), but none of them can be considered as unique superior model (Shamseldin 1997). Owing to difficulties of formulating reasonable non-linear watershed models, recent attempts have resorted to Neural Network (NN) approach for complex hydrologic modeling. In recent years the use of soft computing in the field of hydrological forecasting is gaining ground. The relatively new soft computing technique of Adaptive Neuro-Fuzzy Inference System (ANFIS), developed by Jang (1993) is able to take care of the non-linearity, uncertainty, and vagueness embedded in the system. It is a judicious combination of the Neural Networks and fuzzy systems. It can learn and generalize highly nonlinear and uncertain phenomena due to the embedded neural network (NN). NN is efficient in learning and generalization, and the fuzzy system mimics the cognitive capability of human brain. Hence, ANFIS can learn the complicated processes involved in the basin and correlate the precipitation to the corresponding discharge. In the present study, one step ahead forecasts are made for ten-daily flows, which are mostly required for short term operational planning of multipurpose reservoirs. A

  10. Spatial load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Willis, H.L.; Engel, M.V.; Buri, M.J.

    1995-04-01

    The reliability, efficiency, and economy of a power delivery system depend mainly on how well its substations, transmission lines, and distribution feeders are located within the utility service area, and how well their capacities match power needs in their respective localities. Often, utility planners are forced to commit to sites, rights of way, and equipment capacities year in advance. A necessary element of effective expansion planning is a forecast of where and how much demand must be served by the future T and D system. This article reports that a three-stage method forecasts with accuracy and detail, allowing meaningful determination of sties and sizes for future substation, transmission, and distribution facilities.

  11. Forecast of auroral activity

    International Nuclear Information System (INIS)

    Lui, A.T.Y.

    2004-01-01

    A new technique is developed to predict auroral activity based on a sample of over 9000 auroral sites identified in global auroral images obtained by an ultraviolet imager on the NASA Polar satellite during a 6-month period. Four attributes of auroral activity sites are utilized in forecasting, namely, the area, the power, and the rates of change in area and power. This new technique is quite accurate, as indicated by the high true skill scores for forecasting three different levels of auroral dissipation during the activity lifetime. The corresponding advanced warning time ranges from 22 to 79 min from low to high dissipation levels

  12. Optimising reservoir operation

    DEFF Research Database (Denmark)

    Ngo, Long le

    Anvendelse af optimeringsteknik til drift af reservoirer er blevet et væsentligt element i vandressource-planlægning og -forvaltning. Traditionelt har reservoirer været styret af heuristiske procedurer for udtag af vand, suppleret i en vis udstrækning af subjektive beslutninger. Udnyttelse af...... reservoirer involverer en lang række interessenter med meget forskellige formål (f.eks. kunstig vanding, vandkraft, vandforsyning mv.), og optimeringsteknik kan langt bedre lede frem til afbalancerede løsninger af de ofte modstridende interesser. Afhandlingen foreslår en række tiltag, hvormed traditionelle...... driftsstrategier kan erstattes af optimale strategier baseret på den nyeste udvikling indenfor computer-baserede beregninger. Hovedbidraget i afhandlingen er udviklingen af et beregningssystem, hvori en simuleringsmodel er koblet til en model for optimering af nogle udvalgte beslutningsvariable, der i særlig grad...

  13. Combining forecasts in short term load forecasting: Empirical ...

    Indian Academy of Sciences (India)

    We present an empirical analysis to show that combination of short term load forecasts leads to better accuracy. We also discuss other aspects of combination, i.e.,distribution of weights, effect of variation in the historical window and distribution of forecast errors. The distribution of forecast errors is analyzed in order to get a ...

  14. Forecasting Housing Approvals in Australia: Do Forecasters Herd?

    DEFF Research Database (Denmark)

    Stadtmann, Georg; Pierdzioch; Rülke

    2012-01-01

    Price trends in housing markets may reflect herding of market participants. A natural question is whether such herding, to the extent that it occurred, reflects herding in forecasts of professional forecasters. Using more than 6,000 forecasts of housing approvals for Australia, we did not find...

  15. Geothermal reservoir engineering

    CERN Document Server

    Grant, Malcolm Alister

    2011-01-01

    As nations alike struggle to diversify and secure their power portfolios, geothermal energy, the essentially limitless heat emanating from the earth itself, is being harnessed at an unprecedented rate.  For the last 25 years, engineers around the world tasked with taming this raw power have used Geothermal Reservoir Engineering as both a training manual and a professional reference.  This long-awaited second edition of Geothermal Reservoir Engineering is a practical guide to the issues and tasks geothermal engineers encounter in the course of their daily jobs. The bo

  16. Session: Reservoir Technology

    Energy Technology Data Exchange (ETDEWEB)

    Renner, Joel L.; Bodvarsson, Gudmundur S.; Wannamaker, Philip E.; Horne, Roland N.; Shook, G. Michael

    1992-01-01

    This session at the Geothermal Energy Program Review X: Geothermal Energy and the Utility Market consisted of five papers: ''Reservoir Technology'' by Joel L. Renner; ''LBL Research on the Geysers: Conceptual Models, Simulation and Monitoring Studies'' by Gudmundur S. Bodvarsson; ''Geothermal Geophysical Research in Electrical Methods at UURI'' by Philip E. Wannamaker; ''Optimizing Reinjection Strategy at Palinpinon, Philippines Based on Chloride Data'' by Roland N. Horne; ''TETRAD Reservoir Simulation'' by G. Michael Shook

  17. CDM Convective Forecast Planning guidance

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The CDM Convective Forecast Planning (CCFP) guidance product provides a foreast of en-route aviation convective hazards. The forecasts are updated every 2 hours and...

  18. Battlescale Forecast Model Sensitivity Study

    National Research Council Canada - National Science Library

    Sauter, Barbara

    2003-01-01

    .... Changes to the surface observations used in the Battlescale Forecast Model initialization led to no significant changes in the resulting forecast values of temperature, relative humidity, wind speed, or wind direction...

  19. Challenges of operational river forecasting

    NARCIS (Netherlands)

    Pagano, T.C.; Wood, A.W.; Ramos, M.H.; Cloke, H.L.; Pappenbreger, F.; Verkade, J.S.

    2014-01-01

    Skillful and timely streamflow forecasts are critically important to water managers and emergency protection services. To provide these forecasts, hydrologists must predict the behavior of complex coupled human–natural systems using incomplete and uncertain information and imperfect models.

  20. Are demand forecasting techniques applicable to libraries?

    OpenAIRE

    Sridhar, M. S.

    1984-01-01

    Examines the nature and limitations of demand forecasting, discuses plausible methods of forecasting demand for information, suggests some useful hints for demand forecasting and concludes by emphasizing unified approach to demand forecasting.

  1. Pollutant forecasting error based on persistence of wind direction

    International Nuclear Information System (INIS)

    Cooper, R.E.

    1978-01-01

    The purpose of this report is to provide a means of estimating the reliability of forecasts of downwind pollutant concentrations from atmospheric puff releases. These forecasts are based on assuming the persistence of wind direction as determined at the time of release. This initial forecast will be used to deploy survey teams, to predict population centers that may be affected, and to estimate the amount of time available for emergency response. Reliability of forecasting is evaluated by developing a cumulative probability distribution of error as a function of lapsed time following an assumed release. The cumulative error is determined by comparing the forecast pollutant concentration with the concentration measured by sampling along the real-time meteorological trajectory. It may be concluded that the assumption of meteorological persistence for emergency response is not very good for periods longer than 3 hours. Even within this period, the possibiity for large error exists due to wind direction shifts. These shifts could affect population areas totally different from those areas first indicated

  2. Forecasting inbound tourists in Cambodia

    OpenAIRE

    Tanaka, Kiyoyasu

    2016-01-01

    Forecasting tourism demand is crucial for management decisions in the tourism sector. Estimating a vector autoregressive (VAR) model for monthly visitor arrivals disaggregated by three entry points in Cambodia for the years 2006–2015, I forecast the number of arrivals for years 2016 and 2017. The results show that the VAR model fits well with the data on visitor arrivals for each entry point. Ex post forecasting shows that the forecasts closely match the observed data for visitor arrivals, th...

  3. Streamflow forecast in the Alto do Rio Doce watershed in Brazil, using hydrological and atmospheric model

    Science.gov (United States)

    Silva, J. M.; Saad, S. I.; Palma, G.; Rocha, H.; Palmeira, R. M.; Silva, B. L.; Pessoa, A. A.; Ramos, C. G.; Cecchini, M. A.

    2013-05-01

    Electrical energy in Brazil depends essentially on the streamflow, as hydropowers accounts for up to 79% of the total electrical energy installed capacity. Therefore, streamflow forecasts are very important tools to assist in the planning and operation of Brazilian hydroelectric reservoirs. This study evaluated the performance of a distributed hydrological model, Soil and Water Assessment Tool (SWAT) daily streamflow forecasts into four Reservoirs sited in the Alto do Rio Doce Watershed, in Southeast of Brazil. SWAT model was used with precipitation forecast from the regional meteorological model MM5. The calibration and validation processes of SWAT were accomplished using data from four monitoring stations. The model has been run for the 2010-2012 period, and while the apr/2010-set/2011 period has been used for calibration conducted manually, the validation reached the rest of the period. The manual calibration was conducted by the means of sensibility tests of parameters that control surface runoff and groundwater flow, specially the surlag and alpha_bf, respectively the surface runoff lag coefficient and the baseflow recession constant. The daily and monthly Nash-Sutcliffe, R2 and the mean relative error performance indicators were used to assess the relative performance of the model. Results showed that streamflow forecast was very similar toobservations, except in reservoirs with lower drainage areas, where the model did not simulated the beginning of the flood (Dec-Feb). The streamflow forecasts was strongly dependent on the quality of precipitation forecasts used. Given that no correction in the simulated rainfall by the MM5 model in the Alto do Rio Doce watershed has been conducted and no automated calibration method was applied to the parameters of the hydrologic model, we can conclude that the application of the SWAT hydrologic model employing the output data from the MM5 atmospheric model for the streamflow forecast was shown to be a tool of great

  4. Valuing year-to-go hydrologic forecast improvements for a peaking hydropower system in the Sierra Nevada

    Science.gov (United States)

    Rheinheimer, David E.; Bales, Roger C.; Oroza, Carlos A.; Lund, Jay R.; Viers, Joshua H.

    2016-05-01

    We assessed the potential value of hydrologic forecasting improvements for a snow-dominated high-elevation hydropower system in the Sierra Nevada of California, using a hydropower optimization model. To mimic different forecasting skill levels for inflow time series, rest-of-year inflows from regression-based forecasts were blended in different proportions with representative inflows from a spatially distributed hydrologic model. The statistical approach mimics the simpler, historical forecasting approach that is still widely used. Revenue was calculated using historical electricity prices, with perfect price foresight assumed. With current infrastructure and operations, perfect hydrologic forecasts increased annual hydropower revenue by 0.14 to 1.6 million, with lower values in dry years and higher values in wet years, or about $0.8 million (1.2%) on average, representing overall willingness-to-pay for perfect information. A second sensitivity analysis found a wider range of annual revenue gain or loss using different skill levels in snow measurement in the regression-based forecast, mimicking expected declines in skill as the climate warms and historical snow measurements no longer represent current conditions. The value of perfect forecasts was insensitive to storage capacity for small and large reservoirs, relative to average inflow, and modestly sensitive to storage capacity with medium (current) reservoir storage. The value of forecasts was highly sensitive to powerhouse capacity, particularly for the range of capacities in the northern Sierra Nevada. The approach can be extended to multireservoir, multipurpose systems to help guide investments in forecasting.

  5. Forecasters' Objectives and Strategies

    DEFF Research Database (Denmark)

    Marinovic, Iván; Ottaviani, Marco; Sørensen, Peter Norman

    2013-01-01

    This chapter develops a unified modeling framework for analyzing the strategic behavior of forecasters. The theoretical model encompasses reputational objectives, competition for the best accuracy, and bias. Also drawing from the extensive lit- erature on analysts, we review the empirical evidenc...

  6. Housing Price Forecastability

    DEFF Research Database (Denmark)

    Bork, Lasse; Møller, Stig Vinther

    2016-01-01

    We examine U.S. housing price forecastability using principal component analysis (PCA), partial least squares (PLS), and sparse PLS (SPLS). We incorporate information from a large panel of 128 economic time series and show that macroeconomic fundamentals have strong predictive power for future mo...

  7. Hydrology and flow forecasting

    NARCIS (Netherlands)

    Vrijling, J.K.; Kwadijk, J.; Van Duivendijk, J.; Van Gelder, P.; Pang, H.; Rao, S.Q.; Wang, G.Q.; Huang, X.Q.

    2002-01-01

    We have studied and applied the statistic model (i.e. MMC) and hydrological models to Upper Yellow River. This report introduces the results and some conclusions from the model. The three models, MMC, MWBM and NAM, have be applied in the research area. The forecasted discharge by the three models

  8. Reference class forecasting

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent

    Underbudgettering og budgetoverskridelser forekommer i et flertal af større bygge- og anlægsprojekter. Problemet skyldes optimisme og/eller strategisk misinformation i budgetteringsprocessen. Reference class forecasting (RCF) er en prognosemetode, som er udviklet for at reducere eller eliminere...

  9. Seasonal streamflow forecasting: experiences with precipitation bias correction and SPI conditioning to improve performance for hydrological events

    Science.gov (United States)

    Ramos, M. H.; Crochemore, L.; Pappenberger, F.; Perrin, C.

    2016-12-01

    Many fields such as drought risk assessment or reservoir management can benefit from seasonal streamflow forecasts. This study presents the results of two analyses aiming to: 1) assess the skill of seasonal precipitation forecasts in France and provide insights into the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times, and 2) evaluate how the conditioning of historical data based on the Standardized Precipitation Index (SPI) from bias-corrected GCM precipitation forecasts can be useful to select traces within the historical data and further improve the forecast of droughts. We evaluated several bias correction approaches and conditioned precipitation scenarios in sixteen catchments in France, with the help of ECMWF System 4 seasonal precipitation forecasts and the GR6J hydrological model. The results show that, in most catchments, raw seasonal precipitation and streamflow forecasts are often sharper than the conventional ESP method. However, they are not significantly better in terms of reliability. Forecast skill is generally improved when applying bias correction. The simple linear scaling of monthly values contributed mainly to increase forecast sharpness and accuracy, while the empirical distribution mapping of daily values was successful in improving forecast reliability. Our results also show that conditioning past observations based on the three-month Standardized Precipitation Index (SPI3) can improve the sharpness of ensemble forecasts based on historical data, while maintaining good reliability. An evaluation of forecast ensembles for low-flow forecasting showed that the SPI3-conditioned ensembles provided reliable forecasts of low-flow duration and deficit volume based on the 80th exceedance percentile. Drought risk forecasting is illustrated for the 2003 drought event.

  10. Air Pollution Forecasts: An Overview

    Directory of Open Access Journals (Sweden)

    Lu Bai

    2018-04-01

    Full Text Available Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  11. GEOS-5 seasonal forecast system

    Science.gov (United States)

    Borovikov, Anna; Cullather, Richard; Kovach, Robin; Marshak, Jelena; Vernieres, Guillaume; Vikhliaev, Yury; Zhao, Bin; Li, Zhao

    2017-09-01

    Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9-month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems.

  12. Air Pollution Forecasts: An Overview.

    Science.gov (United States)

    Bai, Lu; Wang, Jianzhou; Ma, Xuejiao; Lu, Haiyan

    2018-04-17

    Air pollution is defined as a phenomenon harmful to the ecological system and the normal conditions of human existence and development when some substances in the atmosphere exceed a certain concentration. In the face of increasingly serious environmental pollution problems, scholars have conducted a significant quantity of related research, and in those studies, the forecasting of air pollution has been of paramount importance. As a precaution, the air pollution forecast is the basis for taking effective pollution control measures, and accurate forecasting of air pollution has become an important task. Extensive research indicates that the methods of air pollution forecasting can be broadly divided into three classical categories: statistical forecasting methods, artificial intelligence methods, and numerical forecasting methods. More recently, some hybrid models have been proposed, which can improve the forecast accuracy. To provide a clear perspective on air pollution forecasting, this study reviews the theory and application of those forecasting models. In addition, based on a comparison of different forecasting methods, the advantages and disadvantages of some methods of forecasting are also provided. This study aims to provide an overview of air pollution forecasting methods for easy access and reference by researchers, which will be helpful in further studies.

  13. unconventional natural gas reservoirs

    International Nuclear Information System (INIS)

    Correa G, Tomas F; Osorio, Nelson; Restrepo R, Dora P

    2009-01-01

    This work is an exploration about different unconventional gas reservoirs worldwide: coal bed methane, tight gas, shale gas and gas hydrate? describing aspects such as definition, reserves, production methods, environmental issues and economics. The overview also mentioned preliminary studies about these sources in Colombia.

  14. Parallel reservoir simulator computations

    International Nuclear Information System (INIS)

    Hemanth-Kumar, K.; Young, L.C.

    1995-01-01

    The adaptation of a reservoir simulator for parallel computations is described. The simulator was originally designed for vector processors. It performs approximately 99% of its calculations in vector/parallel mode and relative to scalar calculations it achieves speedups of 65 and 81 for black oil and EOS simulations, respectively on the CRAY C-90

  15. The Use of Operational Short and Long Lead-time Hydrologic Forecasts by Water Resources Decision Makers in the Ohio River Valley

    Science.gov (United States)

    Adams, T. E.

    2012-12-01

    The need for hydroclimatic forecasts for water resources systems operations is significant and is clearly growing. Hydroclimatic forecasts consist of two components: first, forecasts of hydrometeorological forcings used to drive hydrologic models and, second, the resulting streamflow and stage forecasts or derivative quantities, such as reservoir inflow volumes or time above (or below) some threshold value. These forecast range from hourly to annual lead-times and include both deterministic and probabilistic formats. In the Ohio River Valley, forecasts are made available by the NOAA/NWS Ohio River Forecast Center to decision makers. These include the general public, local and state emergency managers and other officials, federal agencies, utilities, the navigation industry, and agricultural sector, and others. Hydrologic forecasts are utilized by end-users for widely varying purposes including flood warning and mitigation, reservoir management, and decision making for construction projects, to name a few. This paper will illustrate the range of NWS hydrologic streamflow and stage products that are made publicly available and how some of the forecasts are used during drought or low-flow periods and during episodes of flooding. The methodologies used to generate hydroclimatic forecasts and the complexities found in large-scale operational systems and their impact on forecast robustness will also be discussed.

  16. Influence of break structures on the distribution of radionuclides in bottom sediments of the Kyiv reservoir

    International Nuclear Information System (INIS)

    Shestopalov, V.M.; Lyal'ko, V.I.; Fedorovskij, A.D.; Sirenko, L.A.; Khodorovskij, A.Ya.

    2000-01-01

    We study the distribution of radionuclides in bottom sediments of the Kyiv reservoir on the basis of research of adjacent territory break - block structures with deciphering space-born images and ground measurements and forecast the occurrence of extreme situations due to the redistribution of bottom water flows and sediments of radionuclides

  17. The management of subsurface uncertainty using probabilistic modeling of life cycle production forecasts and cash flows

    International Nuclear Information System (INIS)

    Olatunbosun, O. O.

    1998-01-01

    The subject pertains to the implementation of the full range of subsurface uncertainties in life cycle probabilistic forecasting and its extension to project cash flows using the methodology of probabilities. A new tool has been developed in the probabilistic application of Crystal-Ball which can model reservoir volumetrics, life cycle production forecasts and project cash flows in a single environment. The tool is modular such that the volumetrics and cash flow modules are optional. Production forecasts are often generated by applying a decline equation to single best estimate values of input parameters such as initial potential, decline rate, abandonment rate etc -or sometimes by results of reservoir simulation. This new tool provides a means of implementing the full range of uncertainties and interdependencies of the input parameters into the production forecasts by defining the input parameters as probability density functions, PDFs and performing several iterations to generate an expectation curve forecast. Abandonment rate is implemented in each iteration via a link to an OPEX model. The expectation curve forecast is input into a cash flow model to generate a probabilistic NPV. Base case and sensitivity runs from reservoir simulation can likewise form the basis for a probabilistic production forecast from which a probabilistic cash flow can be generated. A good illustration of the application of this tool is in the modelling of the production forecast for a well that encounters its target reservoirs in OUT/ODT situation and thus has significant uncertainties. The uncertainty in presence and size (if present) of gas cap and dependency between ultimate recovery and initial potential amongst other uncertainties can be easily implemented in the production forecast with this tool. From the expectation curve forecast, a probabilistic NPV can be easily generated. Possible applications of this tool include: i. estimation of range of actual recoverable volumes based

  18. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    D. O. Hitzman; A. K. Stepp; D. M. Dennis; L. R. Graumann

    2003-03-31

    This research program is directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal is to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents. Experimental laboratory work is underway. Microbial cultures have been isolated from produced water samples. Comparative laboratory studies demonstrating in situ production of microbial products as oil recovery agents were conducted in sand packs with natural field waters with cultures and conditions representative of oil reservoirs. Field pilot studies are underway.

  19. Numerical Weather Forecasting at the Savannah River Site

    International Nuclear Information System (INIS)

    Buckley, R.L.

    1999-01-01

    Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations

  20. Numerical Weather Forecasting at the Savannah River Site

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R.L.

    1999-01-26

    Facilities such as the Savannah River Site (SRS), which contain the potential for hazardous atmospheric releases, rely on the predictive capabilities of dispersion models to assess possible emergency response actions. The operational design in relation to domain size and forecast time is presented, along with verification of model results over extended time periods with archived surface observations.

  1. Comparison of random forests and support vector machine for real-time radar-derived rainfall forecasting

    Science.gov (United States)

    Yu, Pao-Shan; Yang, Tao-Chang; Chen, Szu-Yin; Kuo, Chen-Min; Tseng, Hung-Wei

    2017-09-01

    This study aims to compare two machine learning techniques, random forests (RF) and support vector machine (SVM), for real-time radar-derived rainfall forecasting. The real-time radar-derived rainfall forecasting models use the present grid-based radar-derived rainfall as the output variable and use antecedent grid-based radar-derived rainfall, grid position (longitude and latitude) and elevation as the input variables to forecast 1- to 3-h ahead rainfalls for all grids in a catchment. Grid-based radar-derived rainfalls of six typhoon events during 2012-2015 in three reservoir catchments of Taiwan are collected for model training and verifying. Two kinds of forecasting models are constructed and compared, which are single-mode forecasting model (SMFM) and multiple-mode forecasting model (MMFM) based on RF and SVM. The SMFM uses the same model for 1- to 3-h ahead rainfall forecasting; the MMFM uses three different models for 1- to 3-h ahead forecasting. According to forecasting performances, it reveals that the SMFMs give better performances than MMFMs and both SVM-based and RF-based SMFMs show satisfactory performances for 1-h ahead forecasting. However, for 2- and 3-h ahead forecasting, it is found that the RF-based SMFM underestimates the observed radar-derived rainfalls in most cases and the SVM-based SMFM can give better performances than RF-based SMFM.

  2. APPLICATION OF INTEGRATED RESERVOIR MANAGEMENT AND RESERVOIR CHARACTERIZATION

    Energy Technology Data Exchange (ETDEWEB)

    Jack Bergeron; Tom Blasingame; Louis Doublet; Mohan Kelkar; George Freeman; Jeff Callard; David Moore; David Davies; Richard Vessell; Brian Pregger; Bill Dixon; Bryce Bezant

    2000-03-01

    Reservoir performance and characterization are vital parameters during the development phase of a project. Infill drilling of wells on a uniform spacing, without regard to characterization does not optimize development because it fails to account for the complex nature of reservoir heterogeneities present in many low permeability reservoirs, especially carbonate reservoirs. These reservoirs are typically characterized by: (1) large, discontinuous pay intervals; (2) vertical and lateral changes in reservoir properties; (3) low reservoir energy; (4) high residual oil saturation; and (5) low recovery efficiency. The operational problems they encounter in these types of reservoirs include: (1) poor or inadequate completions and stimulations; (2) early water breakthrough; (3) poor reservoir sweep efficiency in contacting oil throughout the reservoir as well as in the nearby well regions; (4) channeling of injected fluids due to preferential fracturing caused by excessive injection rates; and (5) limited data availability and poor data quality. Infill drilling operations only need target areas of the reservoir which will be economically successful. If the most productive areas of a reservoir can be accurately identified by combining the results of geological, petrophysical, reservoir performance, and pressure transient analyses, then this ''integrated'' approach can be used to optimize reservoir performance during secondary and tertiary recovery operations without resorting to ''blanket'' infill drilling methods. New and emerging technologies such as geostatistical modeling, rock typing, and rigorous decline type curve analysis can be used to quantify reservoir quality and the degree of interwell communication. These results can then be used to develop a 3-D simulation model for prediction of infill locations. The application of reservoir surveillance techniques to identify additional reservoir ''pay'' zones

  3. Bathymetry and capacity of Blackfoot Reservoir, Caribou County, Idaho, 2011

    Science.gov (United States)

    Wood, Molly S.; Skinner, Kenneth D.; Fosness, Ryan L.

    2012-01-01

    The U.S. Geological Survey (USGS), in cooperation with the Shoshone-Bannock Tribes, surveyed the bathymetry and selected above-water sections of Blackfoot Reservoir, Caribou County, Idaho, in 2011. Reservoir operators manage releases from Government Dam on Blackfoot Reservoir based on a stage-capacity relation developed about the time of dam construction in the early 1900s. Reservoir operation directly affects the amount of water that is available for irrigation of agricultural land on the Fort Hall Indian Reservation and surrounding areas. The USGS surveyed the below-water sections of the reservoir using a multibeam echosounder and real-time kinematic global positioning system (RTK-GPS) equipment at full reservoir pool in June 2011, covering elevations from 6,090 to 6,119 feet (ft) above the North American Vertical Datum of 1988 (NAVD 88). The USGS used data from a light detection and ranging (LiDAR) survey performed in 2000 to map reservoir bathymetry from 6,116 to 6,124 ft NAVD 88, which were mostly in depths too shallow to measure with the multibeam echosounder, and most of the above-water section of the reservoir (above 6,124 ft NAVD 88). Selected points and bank erosional features were surveyed by the USGS using RTK-GPS and a total station at low reservoir pool in September 2011 to supplement and verify the LiDAR data. The stage-capacity relation was revised and presented in a tabular format. The datasets show a 2.0-percent decrease in capacity from the original survey, due to sedimentation or differences in accuracy between surveys. A 1.3-percent error also was detected in the previously used capacity table and measured water-level elevation because of questionable reference elevation at monitoring stations near Government Dam. Reservoir capacity in 2011 at design maximum pool of 6,124 ft above NAVD 88 was 333,500 acre-ft.

  4. Decision Support System for Reservoir Management and Operation in Africa

    Science.gov (United States)

    Navar, D. A.

    2016-12-01

    Africa is currently experiencing a surge in dam construction for flood control, water supply and hydropower production, but ineffective reservoir management has caused problems in the region, such as water shortages, flooding and loss of potential hydropower generation. Our research aims to remedy ineffective reservoir management by developing a novel Decision Support System(DSS) to equip water managers with a technical planning tool based on the state of the art in hydrological sciences. The DSS incorporates a climate forecast model, a hydraulic model of the watershed, and an optimization model to effectively plan for the operation of a system of cascade large-scale reservoirs for hydropower production, while treating water supply and flood control as constraints. Our team will use the newly constructed hydropower plants in the Omo Gibe basin of Ethiopia as the test case. Using the basic HIDROTERM software developed in Brazil, the General Algebraic Modeling System (GAMS) utilizes a combination of linear programing (LP) and non-linear programming (NLP) in conjunction with real time hydrologic and energy demand data to optimize the monthly and daily operations of the reservoir system. We compare the DSS model results with the current reservoir operating policy used by the water managers of that region. We also hope the DSS will eliminate the current dangers associated with the mismanagement of large scale water resources projects in Africa.

  5. Load forecasting for supermarket refrigeration

    DEFF Research Database (Denmark)

    Bacher, Peder; Madsen, Henrik; Aalborg Nielsen, Henrik

    This report presents a study of models for forecasting the load for supermarket refrigeration. The data used for building the forecasting models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. The load for refrigeration is the sum of all cabinets in the supermarket, both low and medium temperature cabinets, and spans a period of one year. As input to the forecasting models the ambient temperature observed near the supermarket together with weather forecasts are used. Every hour...... the hourly load for refrigeration for the following 42 hours is forecasted. The forecast models are adaptive linear time-series models which are fitted with a computationally efficient recursive least squares scheme. The dynamic relations between the inputs and the load is modeled by simple transfer...

  6. Modeling of Turbidity Variation in Two Reservoirs Connected by a Water Transfer Tunnel in South Korea

    Directory of Open Access Journals (Sweden)

    Jae Chung Park

    2017-06-01

    Full Text Available The Andong and Imha reservoirs in South Korea are connected by a water transfer tunnel. The turbidity of the Imha reservoir is much higher than that of the Andong reservoir. Thus, it is necessary to examine the movement of turbidity between the two reservoirs via the water transfer tunnel. The aim of this study was to investigate the effect of the water transfer tunnel on the turbidity behavior of the two connecting reservoirs and to further understand the effect of reservoir turbidity distribution as a function of the selective withdrawal depth. This study applied the CE-QUAL-W2, a water quality and 2-dimensional hydrodynamic model, for simulating the hydrodynamic processes of the two reservoirs. Results indicate that, in the Andong reservoir, the turbidity of the released water with the water transfer tunnel was similar to that without the tunnel. However, in the Imha reservoir, the turbidity of the released water with the water transfer tunnel was lower than that without the tunnel. This can be attributed to the higher capacity of the Andong reservoir, which has double the storage of the Imha reservoir. Withdrawal turbidity in the Imha reservoir was investigated using the water transfer tunnel. This study applied three withdrawal selections as elevation (EL. 141.0 m, 146.5 m, and 152.0 m. The highest withdrawal turbidity resulted in EL. 141.0 m, which indicates that the high turbidity current is located at a vertical depth of about 20–30 m because of the density difference. These results will be helpful for understanding the release and selective withdrawal turbidity behaviors for a water transfer tunnel between two reservoirs.

  7. The use of various interplanetary scintillation indices within geomagnetic forecasts

    Directory of Open Access Journals (Sweden)

    E. A. Lucek

    Full Text Available Interplanetary scintillation (IPS, the twinkling of small angular diameter radio sources, is caused by the interaction of the signal with small-scale plasma irregularities in the solar wind. The technique may be used to sense remotely the near-Earth heliosphere and observations of a sufficiently large number of sources may be used to track large-scale disturbances as they propagate from close to the Sun to the Earth. Therefore, such observations have potential for use within geomagnetic forecasts. We use daily data from the Mullard Radio Astronomy Observatory, made available through the World Data Centre, to test the success of geomagnetic forecasts based on IPS observations. The approach discussed here was based on the reduction of the information in a map to a single number or series of numbers. The advantages of an index of this nature are that it may be produced routinely and that it could ideally forecast both the occurrence and intensity of geomagnetic activity. We start from an index that has already been described in the literature, INDEX35. On the basis of visual examination of the data in a full skymap format modifications were made to the way in which the index was calculated. It was hoped that these would lead to an improvement in its forecasting ability. Here we assess the forecasting potential of the index using the value of the correlation coefficient between daily Ap and the IPS index, with IPS leading by 1 day. We also compare the forecast based on the IPS index with forecasts of Ap currently released by the Space Environment Services Center (SESC. Although we find that the maximum improvement achieved is small, and does not represent a significant advance in forecasting ability, the IPS forecasts at this phase of the solar cycle are of a similar quality to those made by SESC.

  8. Methodical bases of geodemographic forecasting

    Directory of Open Access Journals (Sweden)

    Катерина Сегіда

    2016-10-01

    Full Text Available The article deals with methodological features of the forecast of population size and composition. The essence and features of probabilistic demographic forecasting, methods, a component and dynamic ranks are considered; requirements to initial indicators for each type of the forecast are provided. It is noted that geo-demographic forecast is an important component of regional geo-demographic characteristic. Features of the demographic forecast development by component method (recursors of age are given, basic formulae of calculation, including the equation of demographic balance, a formula recursors taking into account gender and age indicators, survival coefficient are presented. The basic methodical principles of the demographic forecast are given by an extrapolation method (dynamic ranks, calculation features by means of the generalized indicators, such as extrapolation on the basis of indicators of an average pure gain, average growth rate and average rate of a gain are presented. To develop population forecast, the method of retrospective extrapolation (for the short-term forecast and a component method (for the mid-term forecast are mostly used. The example of such development by component method for gender and age structure of the population of Kharkiv region with step-by-step explanation of calculation is provided. The example of Kharkiv region’s population forecast development is provided by the method of dynamic ranks. Having carried out calculations of the main forecast indicators by administrative units, it is possible to determine features of further regional demographic development, to reveal internal territorial distinctions in demographic development. Application of separate forecasting methods allows to develop the forecast for certain indicators, however essential a variety, nonlinearity and not stationarity of the processes constituting demographic development forces to look +for new approaches and

  9. Integrated Flood Forecast and Virtual Dam Operation System for Water Resources and Flood Risk Management

    Science.gov (United States)

    Shibuo, Yoshihiro; Ikoma, Eiji; Lawford, Peter; Oyanagi, Misa; Kanauchi, Shizu; Koudelova, Petra; Kitsuregawa, Masaru; Koike, Toshio

    2014-05-01

    While availability of hydrological- and hydrometeorological data shows growing tendency and advanced modeling techniques are emerging, such newly available data and advanced models may not always be applied in the field of decision-making. In this study we present an integrated system of ensemble streamflow forecast (ESP) and virtual dam simulator, which is designed to support river and dam manager's decision making. The system consists of three main functions: real time hydrological model, ESP model, and dam simulator model. In the real time model, the system simulates current condition of river basins, such as soil moisture and river discharges, using LSM coupled distributed hydrological model. The ESP model takes initial condition from the real time model's output and generates ESP, based on numerical weather prediction. The dam simulator model provides virtual dam operation and users can experience impact of dam control on remaining reservoir volume and downstream flood under the anticipated flood forecast. Thus the river and dam managers shall be able to evaluate benefit of priori dam release and flood risk reduction at the same time, on real time basis. Furthermore the system has been developed under the concept of data and models integration, and it is coupled with Data Integration and Analysis System (DIAS) - a Japanese national project for integrating and analyzing massive amount of observational and model data. Therefore it has advantage in direct use of miscellaneous data from point/radar-derived observation, numerical weather prediction output, to satellite imagery stored in data archive. Output of the system is accessible over the web interface, making information available with relative ease, e.g. from ordinary PC to mobile devices. We have been applying the system to the Upper Tone region, located northwest from Tokyo metropolitan area, and we show application example of the system in recent flood events caused by typhoons.

  10. Real-time reservoir geological model updating using the hybrid EnKF and geostatistical technique

    Energy Technology Data Exchange (ETDEWEB)

    Li, H.; Chen, S.; Yang, D. [Regina Univ., SK (Canada). Petroleum Technology Research Centre

    2008-07-01

    Reservoir simulation plays an important role in modern reservoir management. Multiple geological models are needed in order to analyze the uncertainty of a given reservoir development scenario. Ideally, dynamic data should be incorporated into a reservoir geological model. This can be done by using history matching and tuning the model to match the past performance of reservoir history. This study proposed an assisted history matching technique to accelerate and improve the matching process. The Ensemble Kalman Filter (EnKF) technique, which is an efficient assisted history matching method, was integrated with a conditional geostatistical simulation technique to dynamically update reservoir geological models. The updated models were constrained to dynamic data, such as reservoir pressure and fluid saturations, and approaches geologically realistic at each time step by using the EnKF technique. The new technique was successfully applied in a heterogeneous synthetic reservoir. The uncertainty of the reservoir characterization was significantly reduced. More accurate forecasts were obtained from the updated models. 3 refs., 2 figs.

  11. Bathymetry and capacity of Shawnee Reservoir, Oklahoma, 2016

    Science.gov (United States)

    Ashworth, Chad E.; Smith, S. Jerrod; Smith, Kevin A.

    2017-02-13

    Shawnee Reservoir (locally known as Shawnee Twin Lakes) is a man-made reservoir on South Deer Creek with a drainage area of 32.7 square miles in Pottawatomie County, Oklahoma. The reservoir consists of two lakes connected by an equilibrium channel. The southern lake (Shawnee City Lake Number 1) was impounded in 1935, and the northern lake (Shawnee City Lake Number 2) was impounded in 1960. Shawnee Reservoir serves as a municipal water supply, and water is transferred about 9 miles by gravity to a water treatment plant in Shawnee, Oklahoma. Secondary uses of the reservoir are for recreation, fish and wildlife habitat, and flood control. Shawnee Reservoir has a normal-pool elevation of 1,069.0 feet (ft) above North American Vertical Datum of 1988 (NAVD 88). The auxiliary spillway, which defines the flood-pool elevation, is at an elevation of 1,075.0 ft.The U.S. Geological Survey (USGS), in cooperation with the City of Shawnee, has operated a real-time stage (water-surface elevation) gage (USGS station 07241600) at Shawnee Reservoir since 2006. For the period of record ending in 2016, this gage recorded a maximum stage of 1,078.1 ft on May 24, 2015, and a minimum stage of 1,059.1 ft on April 10–11, 2007. This gage did not report reservoir storage prior to this report (2016) because a sufficiently detailed and thoroughly documented bathymetric (reservoir-bottom elevation) survey and corresponding stage-storage relation had not been published. A 2011 bathymetric survey with contours delineated at 5-foot intervals was published in Oklahoma Water Resources Board (2016), but that publication did not include a stage-storage relation table. The USGS, in cooperation with the City of Shawnee, performed a bathymetric survey of Shawnee Reservoir in 2016 and released the bathymetric-survey data in 2017. The purposes of the bathymetric survey were to (1) develop a detailed bathymetric map of the reservoir and (2) determine the relations between stage and reservoir storage

  12. EROSION RATE OF RESERVOIR DEPOSIT AS REVEALED BY LABORATORY EXPERIMENT

    Directory of Open Access Journals (Sweden)

    A. S. Amar

    2012-06-01

    Full Text Available The construction of dams and reservoirs in a river can give significant impacts on its flow of water and sediment, and can cause long-term morphological changes on the river. Reservoir sedimentation can reduce a reservoir’s effective flood control volume, and in some severe cases can cause overtopping during floods. Sediment deposition against a dam can reduce its stability, and affect the operation of low-level outlet works, gates, and valves. The abrasive action of sediment particles can roughen the surface of release facilities and can cause cavitations and vibration. Sedimentation can also affect a reservoir’s water quality, and reduce its flood control, water supply, hydropower, and recreation benefits. Consequently, taking sedimentation into consideration not only in the planning and design, but also in the operation and maintenance of a dam and reservoir is important. Keywords: Erosion rate, reservoir deposit, shear stress.

  13. Forecasting Turbine Icing Events

    DEFF Research Database (Denmark)

    Davis, Neil; Hahmann, Andrea N.; Clausen, Niels-Erik

    2012-01-01

    In this study, we present a method for forecasting icing events. The method is validated at two European wind farms in with known icing events. The icing model used was developed using current ice accretion methods, and newly developed ablation algorithms. The model is driven by inputs from the WRF...... mesoscale model, allowing for both climatological estimates of icing and short term icing forecasts. The current model was able to detect periods of icing reasonably well at the warmer site. However at the cold climate site, the model was not able to remove ice quickly enough leading to large ice...... accumulations, which have not been seen in observations. In addition to the model evaluation we were able to investigate the potential occurrence of ice induced power loss at two wind parks in Europe using observed data. We found that the potential loss during an icing event is large even when the turbine...

  14. Forecasting Infectious Disease Outbreaks

    Science.gov (United States)

    Shaman, J. L.

    2015-12-01

    Dynamic models of infectious disease systems abound and are used to study the epidemiological characteristics of disease outbreaks, the ecological mechanisms affecting transmission, and the suitability of various control and intervention strategies. The dynamics of disease transmission are non-linear and consequently difficult to forecast. Here, we describe combined model-inference frameworks developed for the prediction of infectious diseases. We show that accurate and reliable predictions of seasonal influenza outbreaks can be made using a mathematical model representing population-level influenza transmission dynamics that has been recursively optimized using ensemble data assimilation techniques and real-time estimates of influenza incidence. Operational real-time forecasts of influenza and other infectious diseases have been and are currently being generated.

  15. Forecasting carbon dioxide emissions.

    Science.gov (United States)

    Zhao, Xiaobing; Du, Ding

    2015-09-01

    This study extends the literature on forecasting carbon dioxide (CO2) emissions by applying the reduced-form econometrics approach of Schmalensee et al. (1998) to a more recent sample period, the post-1997 period. Using the post-1997 period is motivated by the observation that the strengthening pace of global climate policy may have been accelerated since 1997. Based on our parameter estimates, we project 25% reduction in CO2 emissions by 2050 according to an economic and population growth scenario that is more consistent with recent global trends. Our forecasts are conservative due to that we do not have sufficient data to fully take into account recent developments in the global economy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  16. Deduction of reservoir operating rules for application in global hydrological models

    Directory of Open Access Journals (Sweden)

    H. M. Coerver

    2018-01-01

    Full Text Available A big challenge in constructing global hydrological models is the inclusion of anthropogenic impacts on the water cycle, such as caused by dams. Dam operators make decisions based on experience and often uncertain information. In this study information generally available to dam operators, like inflow into the reservoir and storage levels, was used to derive fuzzy rules describing the way a reservoir is operated. Using an artificial neural network capable of mimicking fuzzy logic, called the ANFIS adaptive-network-based fuzzy inference system, fuzzy rules linking inflow and storage with reservoir release were determined for 11 reservoirs in central Asia, the US and Vietnam. By varying the input variables of the neural network, different configurations of fuzzy rules were created and tested. It was found that the release from relatively large reservoirs was significantly dependent on information concerning recent storage levels, while release from smaller reservoirs was more dependent on reservoir inflows. Subsequently, the derived rules were used to simulate reservoir release with an average Nash–Sutcliffe coefficient of 0.81.

  17. Deduction of reservoir operating rules for application in global hydrological models

    Science.gov (United States)

    Coerver, Hubertus M.; Rutten, Martine M.; van de Giesen, Nick C.

    2018-01-01

    A big challenge in constructing global hydrological models is the inclusion of anthropogenic impacts on the water cycle, such as caused by dams. Dam operators make decisions based on experience and often uncertain information. In this study information generally available to dam operators, like inflow into the reservoir and storage levels, was used to derive fuzzy rules describing the way a reservoir is operated. Using an artificial neural network capable of mimicking fuzzy logic, called the ANFIS adaptive-network-based fuzzy inference system, fuzzy rules linking inflow and storage with reservoir release were determined for 11 reservoirs in central Asia, the US and Vietnam. By varying the input variables of the neural network, different configurations of fuzzy rules were created and tested. It was found that the release from relatively large reservoirs was significantly dependent on information concerning recent storage levels, while release from smaller reservoirs was more dependent on reservoir inflows. Subsequently, the derived rules were used to simulate reservoir release with an average Nash-Sutcliffe coefficient of 0.81.

  18. Uranium price forecasting methods

    International Nuclear Information System (INIS)

    Fuller, D.M.

    1994-01-01

    This article reviews a number of forecasting methods that have been applied to uranium prices and compares their relative strengths and weaknesses. The methods reviewed are: (1) judgemental methods, (2) technical analysis, (3) time-series methods, (4) fundamental analysis, and (5) econometric methods. Historically, none of these methods has performed very well, but a well-thought-out model is still useful as a basis from which to adjust to new circumstances and try again

  19. Statistical methods for forecasting

    CERN Document Server

    Abraham, Bovas

    2009-01-01

    The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists."This book, it must be said, lives up to the words on its advertising cover: ''Bridging the gap between introductory, descriptive approaches and highly advanced theoretical treatises, it provides a practical, intermediate level discussion of a variety of forecasting tools, and explains how they relate to one another, both in theory and practice.'' It does just that!"-Journal of the Royal Statistical Society"A well-written work that deals with statistical methods and models that can be used to produce short-term forecasts, this book has wide-ranging applications. It could be used in the context of a study of regression, forecasting, and time series ...

  20. PyForecastTools

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

    The PyForecastTools package provides Python routines for calculating metrics for model validation, forecast verification and model comparison. For continuous predictands the package provides functions for calculating bias (mean error, mean percentage error, median log accuracy, symmetric signed bias), and for calculating accuracy (mean squared error, mean absolute error, mean absolute scaled error, normalized RMSE, median symmetric accuracy). Convenience routines to calculate the component parts (e.g. forecast error, scaled error) of each metric are also provided. To compare models the package provides: generic skill score; percent better. Robust measures of scale including median absolute deviation, robust standard deviation, robust coefficient of variation and the Sn estimator are all provided by the package. Finally, the package implements Python classes for NxN contingency tables. In the case of a multi-class prediction, accuracy and skill metrics such as proportion correct and the Heidke and Peirce skill scores are provided as object methods. The special case of a 2x2 contingency table inherits from the NxN class and provides many additional metrics for binary classification: probability of detection, probability of false detection, false alarm ration, threat score, equitable threat score, bias. Confidence intervals for many of these quantities can be calculated using either the Wald method or Agresti-Coull intervals.

  1. Climate Change Assessment of Precipitation in Tandula Reservoir System

    Science.gov (United States)

    Jaiswal, Rahul Kumar; Tiwari, H. L.; Lohani, A. K.

    2018-02-01

    The precipitation is the principle input of hydrological cycle affect availability of water in spatial and temporal scale of basin due to widely accepted climate change. The present study deals with the statistical downscaling using Statistical Down Scaling Model for rainfall of five rain gauge stations (Ambagarh, Bhanpura, Balod, Chamra and Gondli) in Tandula, Kharkhara and Gondli reservoirs of Chhattisgarh state of India to forecast future rainfall in three different periods under SRES A1B and A2 climatic forcing conditions. In the analysis, twenty-six climatic variables obtained from National Centers for Environmental Prediction were used and statistically tested for selection of best-fit predictors. The conditional process based statistical correlation was used to evolve multiple linear relations in calibration for period of 1981-1995 was tested with independent data of 1996-2003 for validation. The developed relations were further used to predict future rainfall scenarios for three different periods 2020-2035 (FP-1), 2046-2064 (FP-2) and 2081-2100 (FP-3) and compared with monthly rainfalls during base period (1981-2003) for individual station and all three reservoir catchments. From the analysis, it has been found that most of the rain gauge stations and all three reservoir catchments may receive significant less rainfall in future. The Thiessen polygon based annual and seasonal rainfall for different catchments confirmed a reduction of seasonal rainfall from 5.1 to 14.1% in Tandula reservoir, 11-19.2% in Kharkhara reservoir and 15.1-23.8% in Gondli reservoir. The Gondli reservoir may be affected the most in term of water availability in future prediction periods.

  2. Thermoelastic properties of the Rotokawa Andesite: A geothermal reservoir constraint

    Science.gov (United States)

    Siratovich, P. A.; von Aulock, F. W.; Lavallée, Y.; Cole, J. W.; Kennedy, B. M.; Villeneuve, M. C.

    2015-08-01

    Knowledge of the thermal properties of geothermal reservoir rocks is essential to constraining important engineering concerns such as wellbore stability, reservoir forecasting and stimulation procedures. The thermo-mechanical evolution of geological material is also important to assess when considering natural processes such as magmatic dyke propagation, contact metamorphism and magma/lava emplacement and cooling effects. To better constrain these properties in the geothermal reservoir, thermal measurements were carried out on core samples from production wells drilled in the Rotokawa Andesite geothermal reservoir, located in the Taupo Volcanic Zone, New Zealand. Linear thermal expansion testing, thermogravimetric analysis, and differential scanning calorimetry were used, employing experimental heating rates of 2, 5 and 20 °C/min. Thermal property analyses can elucidate whether thermal expansion values measured under varied heating (and cooling) rates are rate dependent and if thermo-chemical reactions influence the resultant expansivity. Measured thermal expansion coefficients of the Rotokawa Andesite are shown not to be heating rate dependent. We have also found that significant thermochemical reactions occur during heating above 500 °C resulting in non-reversible changes to the thermomechanical properties. The combined thermogravimetric, calorimetric and thermomechanical analysis allows insight to the reactions occurring and how the thermomechanical properties are affected at high temperature. We incorporated results of tensile strength testing on the Rotokawa Andesite to apply our thermal property measurements to a one-dimensional thermal stress model. The developed model provides a failure criterion for the Rotokawa Andesite under thermal stress. The importance of this study is to further understand the critical heating and cooling rates at which thermal stress may cause cracking within the Rotokawa reservoir. Thermal cracking in the reservoir can be

  3. Synergizing Crosswell Seismic and Electromagnetic Techniques for Enhancing Reservoir Characterization

    KAUST Repository

    Katterbauer, Klemens

    2015-11-18

    Increasing complexity of hydrocarbon projects and the request for higher recovery rates have driven the oil-and-gas industry to look for a more-detailed understanding of the subsurface formation to optimize recovery of oil and profitability. Despite the significant successes of geophysical techniques in determining changes within the reservoir, the benefits from individually mapping the information are limited. Although seismic techniques have been the main approach for imaging the subsurface, the weak density contrast between water and oil has made electromagnetic (EM) technology an attractive complement to improve fluid distinction, especially for high-saline water. This crosswell technology assumes greater importance for obtaining higher-resolution images of the interwell regions to more accurately characterize the reservoir and track fluid-front developments. In this study, an ensemble-Kalman-based history-matching framework is proposed for directly incorporating crosswell time-lapse seismic and EM data into the history-matching process. The direct incorporation of the time-lapse seismic and EM data into the history-matching process exploits the complementarity of these data to enhance subsurface characterization, to incorporate interwell information, and to avoid biases that may be incurred from separate inversions of the geophysical data for attributes. An extensive analysis with 2D and realistic 3D reservoirs illustrates the robustness and enhanced forecastability of critical reservoir variables. The 2D reservoir provides a better understanding of the connection between fluid discrimination and enhanced history matches, and the 3D reservoir demonstrates its applicability to a realistic reservoir. History-matching enhancements (in terms of reduction in the history-matching error) when incorporating both seismic and EM data averaged approximately 50% for the 2D case, and approximately 30% for the 3D case, and permeability estimates were approximately 25

  4. Work reservoirs in thermodynamics

    Science.gov (United States)

    Anacleto, Joaquim

    2010-05-01

    We stress the usefulness of the work reservoir in the formalism of thermodynamics, in particular in the context of the first law. To elucidate its usefulness, the formalism is then applied to the Joule expansion and other peculiar and instructive experimental situations, clarifying the concepts of configuration and dissipative work. The ideas and discussions presented in this study are primarily intended for undergraduate students, but they might also be useful to graduate students, researchers and teachers.

  5. A unique application of the instream flow incremental methodology (IFIM) to predict impacts on riverine aquatic habitat, resulting from construction of a proposed hydropower reservoir

    International Nuclear Information System (INIS)

    Foote, P.S.

    1999-01-01

    The City of Harrisburg, Pennsylvania, proposed to construct a new low-head hydroelectric project on the Susquehanna River in the central part of the state in 1986, about 108 km upstream of the river mouth. As part of the licensing process, the city was required by the Federal Energy Regulatory Commission to carry out studies that would forecast the impacts on riverine aquatic habitat as a result of construction of the proposed 13 km long by 1.5 km wide reservoir. The methodology selected by the city and its consultants was to use the IFIM to model the habitat conditions in the project reach both before and after construction of the proposed reservoir.The IFIM is usually used to model instream flow releases downstream of dams and diversions, and had not been used before to model habitat conditions within the proposed reservoir area. The study team hydraulically modelled the project reach using existing hydraulic data, and a HEC-2 backwater analysis to determine post-project water surface elevations. The IFG-4 model was used to simulate both pre- and post-project water velocities, by distributing velocities across transects based on known discharges and cell depth. Effects on aquatic habitat were determined using the IFIM PHABSIM program, in which criteria for several evaluation species and life stages were used to yield estimates of Weighted Usable Area. The analysis showed, based on trends in WUA from pre- and post-project conditions, that habitat conditions would improve for several species and life stages, and would be negatively affected for fewer life stages and species. Some agency concerns that construction of the proposed reservoir would have significant adverse effects on the resident and anadromous fish populations were responded to using these results

  6. Tsengwen Reservoir Watershed Hydrological Flood Simulation Under Global Climate Change Using the 20 km Mesh Meteorological Research Institute Atmospheric General Circulation Model (MRI-AGCM

    Directory of Open Access Journals (Sweden)

    Nobuaki Kimura

    2014-01-01

    Full Text Available Severe rainstorms have occurred more frequently in Taiwan over the last decade. To understand the flood characteristics of a local region under climate change, a hydrological model simulation was conducted for the Tsengwen Reservoir watershed. The model employed was the Integrated Flood Analysis System (IFAS, which has a conceptual, distributed rainfall-runoff analysis module and a GIS data-input function. The high-resolution rainfall data for flood simulation was categorized into three terms: 1979 - 2003 (Present, 2015 - 2039 (Near-future, and 2075 - 2099 (Future, provided by the Meteorological Research Institute atmospheric general circulation model (MRI-AGCM. Ten extreme rainfall (top ten events were selected for each term in descending order of total precipitation volume. Due to the small watershed area the MRI-AGCM3.2S data was downsized into higher resolution data using the Weather Research and Forecasting Model. The simulated discharges revealed that most of the Near-future and Future peaks caused by extreme rainfall increased compared to the Present peak. These ratios were 0.8 - 1.6 (Near-future/Present and 0.9 - 2.2 (Future/Present, respectively. Additionally, we evaluated how these future discharges would affect the reservoir¡¦s flood control capacity, specifically the excess water volume required to be stored while maintaining dam releases up to the dam¡¦s spillway capacity or the discharge peak design for flood prevention. The results for the top ten events show that the excess water for the Future term exceeded the reservoir¡¦s flood control capacity and was approximately 79.6 - 87.5% of the total reservoir maximum capacity for the discharge peak design scenario.

  7. Optimization In Searching Daily Rule Curve At Mosul Regulating Reservoir, North Iraq Using Genetic Algorithms

    Directory of Open Access Journals (Sweden)

    Thair M. Al-Taiee

    2013-05-01

    Full Text Available To obtain optimal operating rules for storage reservoirs, large numbers of simulation and optimization models have been developed over the past several decades, which vary significantly in their mechanisms and applications. Rule curves are guidelines for long term reservoir operation. An efficient technique is required to find the optimal rule curves that can mitigate water shortage in long term operation. The investigation of developed Genetic Algorithm (GA technique, which is an optimization approach base on the mechanics of natural selection, derived from the theory of natural evolution, was carried out to through the application to predict the daily rule curve of  Mosul regulating reservoir in Iraq.  Record daily inflows, outflow, water level in the reservoir for 19 year (1986-1990 and (1994-2007 were used in the developed model for assessing the optimal reservoir operation. The objective function is set to minimize the annual sum of squared deviation from the desired downstream release and desired storage volume in the reservoir. The decision variables are releases, storage volume, water level and outlet (demand from the reservoir. The results of the GA model gave a good agreement during the comparison with the actual rule curve and the designed rating curve of the reservoir. The simulated result shows that GA-derived policies are promising and competitive and can be effectively used for daily reservoir operation in addition to the rational monthly operation and predicting also rating curve of reservoirs.

  8. The Role of Rainfall Variability in Reservoir Storage Management at ...

    African Journals Online (AJOL)

    Statistical analysis of hydro-meteorological data (rainfall, inflow, reservoir storage and turbine release) at Shiroro dam were carried out with the aim of detecting spatio-temporal trends. Correlation and regression analysis were used to develop models for the variables. The correlation of between 0.120 and 0.774 revealed ...

  9. Evolving forecasting classifications and applications in health forecasting

    Directory of Open Access Journals (Sweden)

    Soyiri IN

    2012-05-01

    Full Text Available Ireneous N Soyiri1,2, Daniel D Reidpath11Global Public Health, JCSMHS, MONASH University, Selangor, Malaysia; 2School of Public Health, University of Ghana, Legon, Accra, GhanaAbstract: Health forecasting forewarns the health community about future health situations and disease episodes so that health systems can better allocate resources and manage demand. The tools used for developing and measuring the accuracy and validity of health forecasts commonly are not defined although they are usually adapted forms of statistical procedures. This review identifies previous typologies used in classifying the forecasting methods commonly used in forecasting health conditions or situations. It then discusses the strengths and weaknesses of these methods and presents the choices available for measuring the accuracy of health-forecasting models, including a note on the discrepancies in the modes of validation.Keywords: health forecast, health data, electronic health records, accuracy, cross validation, method, strengths and limitations

  10. Advantageous Reservoir Characterization Technology in Extra Low Permeability Oil Reservoirs

    Directory of Open Access Journals (Sweden)

    Yutian Luo

    2017-01-01

    Full Text Available This paper took extra low permeability reservoirs in Dagang Liujianfang Oilfield as an example and analyzed different types of microscopic pore structures by SEM, casting thin sections fluorescence microscope, and so on. With adoption of rate-controlled mercury penetration, NMR, and some other advanced techniques, based on evaluation parameters, namely, throat radius, volume percentage of mobile fluid, start-up pressure gradient, and clay content, the classification and assessment method of extra low permeability reservoirs was improved and the parameter boundaries of the advantageous reservoirs were established. The physical properties of reservoirs with different depth are different. Clay mineral variation range is 7.0%, and throat radius variation range is 1.81 μm, and start pressure gradient range is 0.23 MPa/m, and movable fluid percentage change range is 17.4%. The class IV reservoirs account for 9.56%, class II reservoirs account for 12.16%, and class III reservoirs account for 78.29%. According to the comparison of different development methods, class II reservoir is most suitable for waterflooding development, and class IV reservoir is most suitable for gas injection development. Taking into account the gas injection in the upper section of the reservoir, the next section of water injection development will achieve the best results.

  11. Analysing UK real estate market forecast disagreement

    OpenAIRE

    McAllister, Patrick; Newell, G.; Matysiak, George

    2005-01-01

    Given the significance of forecasting in real estate investment decisions, this paper investigates forecast uncertainty and disagreement in real estate market forecasts. Using the Investment Property Forum (IPF) quarterly survey amongst UK independent real estate forecasters, these real estate forecasts are compared with actual real estate performance to assess a number of real estate forecasting issues in the UK over 1999-2004, including real estate forecast error, bias and consensus. The re...

  12. Reactive Tracers for Characterizing Fractured Geothermal Reservoirs

    Science.gov (United States)

    Hawkins, Adam J.

    Multi-component tracer tests were conducted at a 10 x 10 m well field located in the Altona Flat Rocks of northern New York. Temperature advancement between two wells separated by 14 m was monitored throughout the well field during progressive heating of the reservoir over 6 d. Multiple approaches to predicting heat transport were applied to field data and compared to temperature rise recorded during reservoir heat-up. Tracer analysis incorporated both an analytical one-dimensional model and a two-dimensional numerical model for non-uniform fractures experiencing "flow-channeling." Modeling efforts demonstrated that estimating heat transfer surface area using a combined inert/adsorbing tracer (cesium-iodide) could provide accurate forecasting of premature thermal breakthrough. In addition, thermally degrading tracer tests were used to monitor inter-well temperature during progressive reservoir heating. Inert tracers alone were, in general, inadequate in forecasting thermal performance. In fact, moment analysis shows that, mathematically, thermal breakthrough is independent of parameters that primarily influence inert tracers. The most accurate prediction of thermal breakthrough using inert tracer alone was produced by treating hydrodynamic dispersion as a truly Fickian process with known and accurate mathematical models. Under this assumption, inert tracer data was matched by solving an inverse problem for non-uniform fracture aperture. Early arrival of the thermal front was predicted at the production, but was less accurate than using a combined inert/adsorbing tracer test. The spatial distribution of fluid flow paths in the plane of the fracture were identified using computational models, Fiber-Optic Distributed Temperature Sensing (FO-DTS), and Ground Penetrating Radar (GPR) imaging of saline tracer flow paths in the target fracture. Without exception, fluid flow was found to be concentrated in a roughly 1 m wide flow channel directly between the two wells. The

  13. A Step Forward to Closing the Loop between Static and Dynamic Reservoir Modeling

    Directory of Open Access Journals (Sweden)

    Cancelliere M.

    2014-12-01

    Full Text Available The current trend for history matching is to find multiple calibrated models instead of a single set of model parameters that match the historical data. The advantage of several current workflows involving assisted history matching techniques, particularly those based on heuristic optimizers or direct search, is that they lead to a number of calibrated models that partially address the problem of the non-uniqueness of the solutions. The importance of achieving multiple solutions is that calibrated models can be used for a true quantification of the uncertainty affecting the production forecasts, which represent the basis for technical and economic risk analysis. In this paper, the importance of incorporating the geological uncertainties in a reservoir study is demonstrated. A workflow, which includes the analysis of the uncertainty associated with the facies distribution for a fluvial depositional environment in the calibration of the numerical dynamic models and, consequently, in the production forecast, is presented. The first step in the workflow was to generate a set of facies realizations starting from different conceptual models. After facies modeling, the petrophysical properties were assigned to the simulation domains. Then, each facies realization was calibrated separately by varying permeability and porosity fields. Data assimilation techniques were used to calibrate the models in a reasonable span of time. Results showed that even the adoption of a conceptual model for facies distribution clearly representative of the reservoir internal geometry might not guarantee reliable results in terms of production forecast. Furthermore, results also showed that realizations which seem fully acceptable after calibration were not representative of the true reservoir internal configuration and provided wrong production forecasts; conversely, realizations which did not show a good fit of the production data could reliably predict the reservoir

  14. ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Mikkelsen, T.; Galmarini, S.; Bianconi, R.; French, S. (eds.)

    2003-11-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

  15. ENSEMBLE methods to reconcile disparate national long range dispersion forecasting

    International Nuclear Information System (INIS)

    Mikkelsen, T.; Galmarini, S.; Bianconi, R.; French, S.

    2003-11-01

    ENSEMBLE is a web-based decision support system for real-time exchange and evaluation of national long-range dispersion forecasts of nuclear releases with cross-boundary consequences. The system is developed with the purpose to reconcile among disparate national forecasts for long-range dispersion. ENSEMBLE addresses the problem of achieving a common coherent strategy across European national emergency management when national long-range dispersion forecasts differ from one another during an accidental atmospheric release of radioactive material. A series of new decision-making 'ENSEMBLE' procedures and Web-based software evaluation and exchange tools have been created for real-time reconciliation and harmonisation of real-time dispersion forecasts from meteorological and emergency centres across Europe during an accident. The new ENSEMBLE software tools is available to participating national emergency and meteorological forecasting centres, which may choose to integrate them directly into operational emergency information systems, or possibly use them as a basis for future system development. (au)

  16. Innovative MIOR Process Utilizing Indigenous Reservoir Constituents

    Energy Technology Data Exchange (ETDEWEB)

    Hitzman, D.O.; Stepp, A.K.

    2003-02-11

    This research program was directed at improving the knowledge of reservoir ecology and developing practical microbial solutions for improving oil production. The goal was to identify indigenous microbial populations which can produce beneficial metabolic products and develop a methodology to stimulate those select microbes with inorganic nutrient amendments to increase oil recovery. This microbial technology has the capability of producing multiple oil-releasing agents. The potential of the system will be illustrated and demonstrated by the example of biopolymer production on oil recovery.

  17. Decision Support on the Sediments Flushing of Aimorés Dam Using Medium-Range Ensemble Forecasts

    Science.gov (United States)

    Mainardi Fan, Fernando; Schwanenberg, Dirk; Collischonn, Walter; Assis dos Reis, Alberto; Alvarado Montero, Rodolfo; Alencar Siqueira, Vinicius

    2015-04-01

    In the present study we investigate the use of medium-range streamflow forecasts in the Doce River basin (Brazil), at the reservoir of Aimorés Hydro Power Plant (HPP). During daily operations this reservoir acts as a "trap" to the sediments that originate from the upstream basin of the Doce River. This motivates a cleaning process called "pass through" to periodically remove the sediments from the reservoir. The "pass through" or "sediments flushing" process consists of a decrease of the reservoir's water level to a certain flushing level when a determined reservoir inflow threshold is forecasted. Then, the water in the approaching inflow is used to flush the sediments from the reservoir through the spillway and to recover the original reservoir storage. To be triggered, the sediments flushing operation requires an inflow larger than 3000m³/s in a forecast horizon of 7 days. This lead-time of 7 days is far beyond the basin's concentration time (around 2 days), meaning that the forecasts for the pass through procedure highly depends on Numerical Weather Predictions (NWP) models that generate Quantitative Precipitation Forecasts (QPF). This dependency creates an environment with a high amount of uncertainty to the operator. To support the decision making at Aimorés HPP we developed a fully operational hydrological forecasting system to the basin. The system is capable of generating ensemble streamflow forecasts scenarios when driven by QPF data from meteorological Ensemble Prediction Systems (EPS). This approach allows accounting for uncertainties in the NWP at a decision making level. This system is starting to be used operationally by CEMIG and is the one shown in the present study, including a hindcasting analysis to assess the performance of the system for the specific flushing problem. The QPF data used in the hindcasting study was derived from the TIGGE (THORPEX Interactive Grand Global Ensemble) database. Among all EPS available on TIGGE, three were

  18. Ensemble hydromoeteorological forecasting in Denmark

    DEFF Research Database (Denmark)

    Lucatero Villasenor, Diana

    of the main sources of uncertainty in hydrological forecasts. This is the reason why substantiated efforts to include information from Numerical Weather Predictors (NWP) or General Circulation Models (GCM) have been made over the last couple of decades. The present thesis expects to advance the field...... forecasts only about 15% and ET0 being the lowest at 15% for some months. The lowest skill of ET0 can be attributable to the combination of both T and incoming shortwave radiation (ISWR) bias from the GCM in addition to the added uncertainty for the model of the ET0 chosen (Makkink formula). Attempts...... steps. First, GCM-based streamflow forecasts exhibit biases that increase with lead time and, although these forecasts are sharper than the ESP forecasts, these biases lead to lower accuracy relative to ESP forecasts, especially at lead times larger than two months. Corrected GCM-based streamflow...

  19. Evaluation of Probabilistic Disease Forecasts.

    Science.gov (United States)

    Hughes, Gareth; Burnett, Fiona J

    2017-10-01

    The statistical evaluation of probabilistic disease forecasts often involves calculation of metrics defined conditionally on disease status, such as sensitivity and specificity. However, for the purpose of disease management decision making, metrics defined conditionally on the result of the forecast-predictive values-are also important, although less frequently reported. In this context, the application of scoring rules in the evaluation of probabilistic disease forecasts is discussed. An index of separation with application in the evaluation of probabilistic disease forecasts, described in the clinical literature, is also considered and its relation to scoring rules illustrated. Scoring rules provide a principled basis for the evaluation of probabilistic forecasts used in plant disease management. In particular, the decomposition of scoring rules into interpretable components is an advantageous feature of their application in the evaluation of disease forecasts.

  20. Design of a lube oil reservoir by using flow calculations

    Energy Technology Data Exchange (ETDEWEB)

    Rinkinen, J.; Alfthan, A. [Institute of Hydraulics and Automation IHA, Tampere University of Technology, Tampere (Finland)] Suominen, J. [Institute of Energy and Process Engineering, Tampere University of Technology, Tampere (Finland); Airaksinen, A.; Antila, K. [R and D Engineer Safematic Oy, Muurame (Finland)

    1997-12-31

    The volume of usual oil reservoir for lubrication oil systems is designed by the traditional rule of thumb so that the total oil volume is theoretically changed in every 30 minutes by rated pumping capacity. This is commonly used settling time for air, water and particles to separate by gravity from the oil returning of the bearings. This leads to rather big volumes of lube oil reservoirs, which are sometimes difficult to situate in different applications. In this presentation traditionally sized lube oil reservoir (8 m{sup 3}) is modelled in rectangular coordinates and laminar oil flow is calculated by using FLUENT software that is based on finite difference method. The results of calculation are velocity and temperature fields inside the reservoir. The velocity field is used to visualize different particle paths through the reservoir. Particles that are studied by the model are air bubbles and water droplets. The interest of the study has been to define the size of the air bubbles that are released and the size of the water droplets that are separated in the reservoir. The velocity field is also used to calculate the modelled circulating time of the oil volume which is then compared with the theoretical circulating time that is obtained from the rated pump flow. These results have been used for designing a new lube oil reservoir. This reservoir has also been modelled and optimized by the aid of flow calculations. The best shape of the designed reservoir is constructed in real size for empirical measurements. Some results of the oil flow measurements are shown. (orig.) 7 refs.

  1. IEA Wind Task 36 Forecasting

    Science.gov (United States)

    Giebel, Gregor; Cline, Joel; Frank, Helmut; Shaw, Will; Pinson, Pierre; Hodge, Bri-Mathias; Kariniotakis, Georges; Sempreviva, Anna Maria; Draxl, Caroline

    2017-04-01

    Wind power forecasts have been used operatively for over 20 years. Despite this fact, there are still several possibilities to improve the forecasts, both from the weather prediction side and from the usage of the forecasts. The new International Energy Agency (IEA) Task on Wind Power Forecasting tries to organise international collaboration, among national weather centres with an interest and/or large projects on wind forecast improvements (NOAA, DWD, UK MetOffice, …) and operational forecaster and forecast users. The Task is divided in three work packages: Firstly, a collaboration on the improvement of the scientific basis for the wind predictions themselves. This includes numerical weather prediction model physics, but also widely distributed information on accessible datasets for verification. Secondly, we will be aiming at an international pre-standard (an IEA Recommended Practice) on benchmarking and comparing wind power forecasts, including probabilistic forecasts aiming at industry and forecasters alike. This WP will also organise benchmarks, in cooperation with the IEA Task WakeBench. Thirdly, we will be engaging end users aiming at dissemination of the best practice in the usage of wind power predictions, especially probabilistic ones. The Operating Agent is Gregor Giebel of DTU, Co-Operating Agent is Joel Cline of the US Department of Energy. Collaboration in the task is solicited from everyone interested in the forecasting business. We will collaborate with IEA Task 31 Wakebench, which developed the Windbench benchmarking platform, which this task will use for forecasting benchmarks. The task runs for three years, 2016-2018. Main deliverables are an up-to-date list of current projects and main project results, including datasets which can be used by researchers around the world to improve their own models, an IEA Recommended Practice on performance evaluation of probabilistic forecasts, a position paper regarding the use of probabilistic forecasts

  2. Earthquake forecasting and its verification

    Directory of Open Access Journals (Sweden)

    J. R. Holliday

    2005-01-01

    Full Text Available No proven method is currently available for the reliable short time prediction of earthquakes (minutes to months. However, it is possible to make probabilistic hazard assessments for earthquake risk. In this paper we discuss a new approach to earthquake forecasting based on a pattern informatics (PI method which quantifies temporal variations in seismicity. The output, which is based on an association of small earthquakes with future large earthquakes, is a map of areas in a seismogenic region ('hotspots'' where earthquakes are forecast to occur in a future 10-year time span. This approach has been successfully applied to California, to Japan, and on a worldwide basis. Because a sharp decision threshold is used, these forecasts are binary--an earthquake is forecast either to occur or to not occur. The standard approach to the evaluation of a binary forecast is the use of the relative (or receiver operating characteristic (ROC diagram, which is a more restrictive test and less subject to bias than maximum likelihood tests. To test our PI method, we made two types of retrospective forecasts for California. The first is the PI method and the second is a relative intensity (RI forecast based on the hypothesis that future large earthquakes will occur where most smaller earthquakes have occurred in the recent past. While both retrospective forecasts are for the ten year period 1 January 2000 to 31 December 2009, we performed an interim analysis 5 years into the forecast. The PI method out performs the RI method under most circumstances.

  3. Medium-range fire weather forecasts

    Science.gov (United States)

    J.O. Roads; K. Ueyoshi; S.C. Chen; J. Alpert; F. Fujioka

    1991-01-01

    The forecast skill of theNational Meteorological Center's medium range forecast (MRF) numerical forecasts of fire weather variables is assessed for the period June 1,1988 to May 31,1990. Near-surface virtual temperature, relative humidity, wind speed and a derived fire weather index (FWI) are forecast well by the MRF model. However, forecast relative humidity has...

  4. Geothermal reservoir management

    Energy Technology Data Exchange (ETDEWEB)

    Scherer, C.R.; Golabi, K.

    1978-02-01

    The optimal management of a hot water geothermal reservoir was considered. The physical system investigated includes a three-dimensional aquifer from which hot water is pumped and circulated through a heat exchanger. Heat removed from the geothermal fluid is transferred to a building complex or other facility for space heating. After passing through the heat exchanger, the (now cooled) geothermal fluid is reinjected into the aquifer. This cools the reservoir at a rate predicted by an expression relating pumping rate, time, and production hole temperature. The economic model proposed in the study maximizes discounted value of energy transferred across the heat exchanger minus the discounted cost of wells, equipment, and pumping energy. The real value of energy is assumed to increase at r percent per year. A major decision variable is the production or pumping rate (which is constant over the project life). Other decision variables in this optimization are production timing, reinjection temperature, and the economic life of the reservoir at the selected pumping rate. Results show that waiting time to production and production life increases as r increases and decreases as the discount rate increases. Production rate decreases as r increases and increases as the discount rate increases. The optimal injection temperature is very close to the temperature of the steam produced on the other side of the heat exchanger, and is virtually independent of r and the discount rate. Sensitivity of the decision variables to geohydrological parameters was also investigated. Initial aquifer temperature and permeability have a major influence on these variables, although aquifer porosity is of less importance. A penalty was considered for production delay after the lease is granted.

  5. Forecasting freight flows

    DEFF Research Database (Denmark)

    Lyk-Jensen, Stéphanie

    2011-01-01

    model. The analysis uses a structural relationship to explain the structure of the exchange of the goods—a relationship that can be used in the year of forecast. This article also provides a new methodology for converting monetary aggregates into quantity aggregates. The resulting commodity growth rates....... This article models long-term dynamic physical trade flows and estimates a dynamic panel data model for foreign trade for the EU15 and two countries from the EFTA (European Free Trade Association) 1967–2002. The analysis suggests that a dynamic three-way-effects gravity equation is the best-fitted econometric...

  6. Utility usage forecasting

    Science.gov (United States)

    Hosking, Jonathan R. M.; Natarajan, Ramesh

    2017-08-22

    The computer creates a utility demand forecast model for weather parameters by receiving a plurality of utility parameter values, wherein each received utility parameter value corresponds to a weather parameter value. Determining that a range of weather parameter values lacks a sufficient amount of corresponding received utility parameter values. Determining one or more utility parameter values that corresponds to the range of weather parameter values. Creating a model which correlates the received and the determined utility parameter values with the corresponding weather parameters values.

  7. On the Influence of Weather Forecast Errors in Short-Term Load Forecasting Models

    OpenAIRE

    Fay, D.; Ringwood, John; Condon, M.

    2004-01-01

    Weather information is an important factor in load forecasting models. This weather information usually takes the form of actual weather readings. However, online operation of load forecasting models requires the use of weather forecasts, with associated weather forecast errors. A technique is proposed to model weather forecast errors to reflect current accuracy. A load forecasting model is then proposed which combines the forecasts of several load forecasting models. This approach allows the...

  8. Advances in photonic reservoir computing

    Science.gov (United States)

    Van der Sande, Guy; Brunner, Daniel; Soriano, Miguel C.

    2017-05-01

    We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir's complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.

  9. Effects of reservoirs water level variations on fish recruitment

    Directory of Open Access Journals (Sweden)

    Fabíula T. de Lima

    2017-10-01

    Full Text Available ABSTRACT The construction of hydroelectric power plants has many social and environmental impacts. Among them, the impacts on fish communities, which habitats are drastically modified by dams, with consequences across the ecosystem. This study aimed to assess the influence of water level (WL variations in the reservoirs of the Itá and Machadinho hydroelectric plants on the recruitment of fish species from the upper Uruguay River in southern Brazil. The data analyzed resulted from the WL variation produced exclusively by the hydroelectric plants generation and were collected between the years 2001 and 2012. The results showed significant correlations between the abundance of juvenile fish and the hydrological parameters only for some reproductive guilds. The species that spawn in nests showed, in general, a clear preference for the stability in the WL of the reservoirs, while the species that spawn in macrophytes or that release demersal eggs showed no significant correlation between the abundance of juvenile fish and hydrological parameters. A divergence of results between the two reservoirs was observed between the species that release semi-dense eggs; a positive correlation with a more stable WL was only observed in the Machadinho reservoir. This result can be driven by a wider range of WL variation in Machadinho reservoir.

  10. Multi-data reservoir history matching of crosswell seismic, electromagnetics and gravimetry data

    KAUST Repository

    Katterbauer, Klemens

    2014-01-01

    Reservoir engineering has become of prime importance for oil and gas field development projects. With rising complexity, reservoir simulations and history matching have become critical for fine-tuning reservoir production strategies, improved subsurface formation knowledge and forecasting remaining reserves. The sparse spatial sampling of production data has posed a significant challenge for reducing uncertainty of subsurface parameters. Seismic, electromagnetic and gravimetry techniques have found widespread application in enhancing exploration for oil and gas and monitor reservoirs, however these data have been interpreted and analyzed mostly separately rarely utilizing the synergy effects that may be attainable. With the incorporation of multiple data into the reservoir history matching process there has been the request knowing the impact each incorporated observation has on the estimation. We present multi-data ensemble-based history matching framework for the incorporation of multiple data such as seismic, electromagnetics, and gravimetry for improved reservoir history matching and provide an adjointfree ensemble sensitivity method to compute the impact of each observation on the estimated reservoir parameters. The incorporation of all data sets displays the advantages multiple data may provide for enhancing reservoir understanding and matching, with the impact of each data set on the matching improvement being determined by the ensemble sensitivity method.

  11. Using analogs to generate production forecasts in Faja

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Lugo, Rolando A. [Repsol (Canada)

    2011-07-01

    In the Carabobol Block, extra heavy oil will be produced by cold production from Miocene Morical Member sands. Many parameters such as pressure, temperature, solution gas oil ratio and viscosity variation significantly impact well productivity; unfortunately little information is available on the Carabobol Block. The aim of this paper is to provide a new methodology for using analog data to develop fluid properties correlations and a future production profile. Data from the analog neighbour field in the Orinoco oil belt was used. A methodology using scatter data was successfully applied for the Carabobol Block and fluid composition, a complete PVT and an analytical forecast were found and confirmed with actual laboratory data and a gross numerical model. This study showed that analog data can be used as a first approach to assess initial reservoir conditions and fluid properties and to generate production forecasts.

  12. Flood Forecasting Based on TIGGE Precipitation Ensemble Forecast

    Directory of Open Access Journals (Sweden)

    Jinyin Ye

    2016-01-01

    Full Text Available TIGGE (THORPEX International Grand Global Ensemble was a major part of the THORPEX (Observing System Research and Predictability Experiment. It integrates ensemble precipitation products from all the major forecast centers in the world and provides systematic evaluation on the multimodel ensemble prediction system. Development of meteorologic-hydrologic coupled flood forecasting model and early warning model based on the TIGGE precipitation ensemble forecast can provide flood probability forecast, extend the lead time of the flood forecast, and gain more time for decision-makers to make the right decision. In this study, precipitation ensemble forecast products from ECMWF, NCEP, and CMA are used to drive distributed hydrologic model TOPX. We focus on Yi River catchment and aim to build a flood forecast and early warning system. The results show that the meteorologic-hydrologic coupled model can satisfactorily predict the flow-process of four flood events. The predicted occurrence time of peak discharges is close to the observations. However, the magnitude of the peak discharges is significantly different due to various performances of the ensemble prediction systems. The coupled forecasting model can accurately predict occurrence of the peak time and the corresponding risk probability of peak discharge based on the probability distribution of peak time and flood warning, which can provide users a strong theoretical foundation and valuable information as a promising new approach.

  13. Interactive Forecasting with the National Weather Service River Forecast System

    Science.gov (United States)

    Smith, George F.; Page, Donna

    1993-01-01

    The National Weather Service River Forecast System (NWSRFS) consists of several major hydrometeorologic subcomponents to model the physics of the flow of water through the hydrologic cycle. The entire NWSRFS currently runs in both mainframe and minicomputer environments, using command oriented text input to control the system computations. As computationally powerful and graphically sophisticated scientific workstations became available, the National Weather Service (NWS) recognized that a graphically based, interactive environment would enhance the accuracy and timeliness of NWS river and flood forecasts. Consequently, the operational forecasting portion of the NWSRFS has been ported to run under a UNIX operating system, with X windows as the display environment on a system of networked scientific workstations. In addition, the NWSRFS Interactive Forecast Program was developed to provide a graphical user interface to allow the forecaster to control NWSRFS program flow and to make adjustments to forecasts as necessary. The potential market for water resources forecasting is immense and largely untapped. Any private company able to market the river forecasting technologies currently developed by the NWS Office of Hydrology could provide benefits to many information users and profit from providing these services.

  14. Overview of Hydrometeorologic Forecasting Procedures at BC Hydro

    Science.gov (United States)

    McCollor, D.

    2004-12-01

    Energy utility companies must balance production from limited sources with increasing demand from industrial, business, and residential consumers. The utility planning process requires a balanced, efficient, and effective distribution of energy from source to consumer. Therefore utility planners must consider the impact of weather on energy production and consumption. Hydro-electric companies should be particularly tuned to weather because their source of energy is water, and water supply depends on precipitation. BC Hydro operates as the largest hydro-electric company in western Canada, managing over 30 reservoirs within the province of British Columbia, and generating electricity for 1.6 million people. BC Hydro relies on weather forecasts of watershed precipitation and temperature to drive hydrologic reservoir inflow models and of urban temperatures to meet energy demand requirements. Operations and planning specialists in the company rely on current, value-added weather forecasts for extreme high-inflow events, daily reservoir operations planning, and long-term water resource management. Weather plays a dominant role for BC Hydro financial planners in terms of sensitive economic responses. For example, a two percent change in hydropower generation, due in large part to annual precipitation patterns, results in an annual net change of \\50 million in earnings. A five percent change in temperature produces a \\5 million change in yearly earnings. On a daily basis, significant precipitation events or temperature extremes involve potential profit/loss decisions in the tens of thousands of dollars worth of power generation. These factors are in addition to environmental and societal costs that must be considered equally as part of a triple bottom line reporting structure. BC Hydro water resource managers require improved meteorological information from recent advancements in numerical weather prediction. At BC Hydro, methods of providing meteorological forecast data

  15. Encapsulated microsensors for reservoir interrogation

    Energy Technology Data Exchange (ETDEWEB)

    Scott, Eddie Elmer; Aines, Roger D.; Spadaccini, Christopher M.

    2016-03-08

    In one general embodiment, a system includes at least one microsensor configured to detect one or more conditions of a fluidic medium of a reservoir; and a receptacle, wherein the receptacle encapsulates the at least one microsensor. In another general embodiment, a method include injecting the encapsulated at least one microsensor as recited above into a fluidic medium of a reservoir; and detecting one or more conditions of the fluidic medium of the reservoir.

  16. Effects of Reservoirs Releases on Tailwater Ecology: A Literature Review.

    Science.gov (United States)

    1981-09-01

    Food,- by the shredding and scraping inv,,rtebrates that are involved 31 - ! in the mechanical aspects of leaf decomposition . The fungi and bacte- ria...and leaf - ltter iccompijosition in natural and channelized portions of a rassstream. Pun. Miai. Nat. 99(1) :238-A53. Goeii-ike, I’. ’v. 1if 8 . 1’ad... Decomposition rates of organic matter increase with increasing temperature, resulting in an additional deple- tion of oxygen content. The rate of

  17. Short-term forecasts of energy use and energy supply 2012-2014. Spring 2013; Kortsiktsprognos - Oever energianvaendning och energitillfoersel 2012-2014, Vaaren 2013

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2013-03-15

    This report provides a description of the Swedish energy system in 2011 and an assessment of its development between 2012 - 2014. The forecast shall be interpreted as a consequence of the limitations and assumptions underlying it. Thus, it is important to remember that if any of the conditions or assumptions change, the forecast's results will also change. The forecast is based on economic conditions that have been developed from the National Institute of Economic Trend. Other conditions such as electricity prices, fuel prices, outdoor temperature and inflow into reservoirs are based on information available up to January 2013, when forecasting began.

  18. Sediment pollution characteristics and in situ control in a deep drinking water reservoir.

    Science.gov (United States)

    Zhou, Zizhen; Huang, Tinglin; Li, Yang; Ma, Weixing; Zhou, Shilei; Long, Shenghai

    2017-02-01

    Sediment pollution characteristics, in situ sediment release potential, and in situ inhibition of sediment release were investigated in a drinking water reservoir. Results showed that organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) in sediments increased from the reservoir mouth to the main reservoir. Fraction analysis indicated that nitrogen in ion exchangeable form and NaOH-extractable P (Fe/Al-P) accounted for 43% and 26% of TN and TP in sediments of the main reservoir. The Risk Assessment Code for metal elements showed that Fe and Mn posed high to very high risk. The results of the in situ reactor experiment in the main reservoir showed the same trends as those observed in the natural state of the reservoir in 2011 and 2012; the maximum concentrations of total OC, TN, TP, Fe, and Mn reached 4.42mg/L, 3.33mg/L, 0.22mg/L, 2.56mg/L, and 0.61mg/L, respectively. An in situ sediment release inhibition technology, the water-lifting aerator, was utilized in the reservoir. The results of operating the water-lifting aerator indicated that sediment release was successfully inhibited and that OC, TN, TP, Fe, and Mn in surface sediment could be reduced by 13.25%, 15.23%, 14.10%, 5.32%, and 3.94%, respectively. Copyright © 2016. Published by Elsevier B.V.

  19. Probabilistic energy forecasting: Global Energy Forecasting Competition 2014 and beyond

    DEFF Research Database (Denmark)

    Hong, Tao; Pinson, Pierre; Fan, Shu

    2016-01-01

    The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged fundamenta...... competition with four tracks on load, price, wind and solar forecasting, which attracted 581 participants from 61 countries. We conclude the paper with 12 predictions for the next decade of energy forecasting.......The energy industry has been going through a significant modernization process over the last decade. Its infrastructure is being upgraded rapidly. The supply, demand and prices are becoming more volatile and less predictable than ever before. Even its business model is being challenged...... fundamentally. In this competitive and dynamic environment, many decision-making processes rely on probabilistic forecasts to quantify the uncertain future. Although most of the papers in the energy forecasting literature focus on point or singlevalued forecasts, the research interest in probabilistic energy...

  20. Issues in Forecasting CMEs

    Science.gov (United States)

    Pizzo, V. J.

    2017-12-01

    I will present my view of the current status of space weather forecasting abilities related to CMEs. This talk will address the large-scale aspects, but specifically not energetic particle phenomena. A key point is that all models, whether sophisticated numerical contraptions or quasi-empirical ones, are only as good as the data you feed them. Hence the emphasis will be on observations and analysis methods. First I will review where we stand with regard to the near-Sun quantitative data needed to drive any model, no matter how complex or simple-minded, and I will discuss technological roadblocks that suggest it may be some time before we see any meaningful improvements beyond what we have today. Then I cover issues related to characterizing CME propagation out through the corona and into interplanetary space, as well as to observational limitations in the vicinity of 1 AU. Since none of these observational constraints are likely to be resolved anytime soon, the real challenge is to make more informed use of what is available. Thus, this talk will focus on how we may identify and pursue the most profitable approaches, for both forecast and research applications. The discussion will highlight a number of promising leads, including those related to inclusion of solar backside information, joint magnetograph observations from L5 and Earth, how to use (not just run) ensembles, more rational use of HI observations, and suggestions for using cube-sats for deep space observations of CMEs and MCs.

  1. Global warming forecasts unreliability

    International Nuclear Information System (INIS)

    Baker, A.B.

    1993-01-01

    This paper reports the opinions of a series of experts who have recently commented on the reliability of predictions of global warning in relation to observed and forecasted increases in carbon dioxide emissions. One of the more difficult to explain observations, evidenced through the analysis of past meteorological data, was the rapid increase in global temperature that took place during the period preceding 1940 and which was followed by a gradual decrease, during a thirty year period of heightened industrialization and consumption of fossil fuels, up to 1970 when global temperatures began again to rise rapidly. Variations in solar activity was suggested to explain this apparently anomalous trend in global temperatures. This question as to the existence of a strict correlation between global warming and rises in carbon dioxide emissions, as well as, forecasted increases in concentrations of atmospheric carbon dioxide due to the expected population growth in China are putting a strain on attempts by OECD (Organization for Economic Co-operation and Development) environmental policy makers to gain support for energy tax proposals

  2. Location specific forecasting of maximum and minimum ...

    Indian Academy of Sciences (India)

    . The global NWP models, though able to provide reasonably good short- to medium-range weather forecasts, have comparatively less skill in forecasting surface parameters. It is well known that NWP model forecasts contain systematic biases ...

  3. Global Ensemble Forecast System (GEFS) [1 Deg.

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Ensemble Forecast System (GEFS) is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental...

  4. Improving Local Weather Forecasts for Agricultural Applications

    NARCIS (Netherlands)

    Doeswijk, T.G.; Keesman, K.J.

    2005-01-01

    For controlling agricultural systems, weather forecasts can be of substantial importance. Studies have shown that forecast errors can be reduced in terms of bias and standard deviation using forecasts and meteorological measurements from one specific meteorological station. For agricultural systems

  5. Guidelines for forecasting energy demand

    International Nuclear Information System (INIS)

    Sonino, T.

    1976-11-01

    Four methodologies for forecasting energy demand are reviewed here after considering the role of energy in the economy and the analysis of energy use in different economic sectors. The special case of Israel is considered throughout, and some forecasts for energy demands in the year 2000 are presented. An energy supply mix that may be considered feasible is proposed. (author)

  6. Forecasting the future of biodiversity

    DEFF Research Database (Denmark)

    Fitzpatrick, M. C.; Sanders, Nate; Ferrier, Simon

    2011-01-01

    , but their application to forecasting climate change impacts on biodiversity has been limited. Here we compare forecasts of changes in patterns of ant biodiversity in North America derived from ensembles of single-species models to those from a multi-species modeling approach, Generalized Dissimilarity Modeling (GDM...... climate change impacts on biodiversity....

  7. Forecasting Using Random Subspace Methods

    NARCIS (Netherlands)

    T. Boot (Tom); D. Nibbering (Didier)

    2016-01-01

    textabstractRandom subspace methods are a novel approach to obtain accurate forecasts in high-dimensional regression settings. We provide a theoretical justification of the use of random subspace methods and show their usefulness when forecasting monthly macroeconomic variables. We focus on two

  8. Now, Here's the Weather Forecast...

    Science.gov (United States)

    Richardson, Mathew

    2013-01-01

    The Met Office has a long history of weather forecasting, creating tailored weather forecasts for customers across the world. Based in Exeter, the Met Office is also home to the Met Office Hadley Centre, a world-leading centre for the study of climate change and its potential impacts. Climate information from the Met Office Hadley Centre is used…

  9. Forecasting Macroeconomic Labour Market Flows

    DEFF Research Database (Denmark)

    Wilke, Ralf

    2017-01-01

    Forecasting labour market flows is important for budgeting and decision-making in government departments and public administration. Macroeconomic forecasts are normally obtained from time series data. In this article, we follow another approach that uses individual-level statistical analysis...

  10. Regional-seasonal weather forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Abarbanel, H.; Foley, H.; MacDonald, G.; Rothaus, O.; Rudermann, M.; Vesecky, J.

    1980-08-01

    In the interest of allocating heating fuels optimally, the state-of-the-art for seasonal weather forecasting is reviewed. A model using an enormous data base of past weather data is contemplated to improve seasonal forecasts, but present skills do not make that practicable. 90 references. (PSB)

  11. Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

    Science.gov (United States)

    Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

    2017-04-01

    The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality

  12. Forecasting Flare Activity Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Hernandez, T.

    2017-12-01

    Current operational flare forecasting relies on human morphological analysis of active regions and the persistence of solar flare activity through time (i.e. that the Sun will continue to do what it is doing right now: flaring or remaining calm). In this talk we present the results of applying deep Convolutional Neural Networks (CNNs) to the problem of solar flare forecasting. CNNs operate by training a set of tunable spatial filters that, in combination with neural layer interconnectivity, allow CNNs to automatically identify significant spatial structures predictive for classification and regression problems. We will start by discussing the applicability and success rate of the approach, the advantages it has over non-automated forecasts, and how mining our trained neural network provides a fresh look into the mechanisms behind magnetic energy storage and release.

  13. Effective Feature Preprocessing for Time Series Forecasting

    DEFF Research Database (Denmark)

    Zhao, Junhua; Dong, Zhaoyang; Xu, Zhao

    2006-01-01

    Time series forecasting is an important area in data mining research. Feature preprocessing techniques have significant influence on forecasting accuracy, therefore are essential in a forecasting model. Although several feature preprocessing techniques have been applied in time series forecasting...... performance in time series forecasting. It is demonstrated in our experiment that, effective feature preprocessing can significantly enhance forecasting accuracy. This research can be a useful guidance for researchers on effectively selecting feature preprocessing techniques and integrating them with time...

  14. Method of forecasting power distribution

    International Nuclear Information System (INIS)

    Kaneto, Kunikazu.

    1981-01-01

    Purpose: To obtain forecasting results at high accuracy by reflecting the signals from neutron detectors disposed in the reactor core on the forecasting results. Method: An on-line computer transfers, to a simulator, those process data such as temperature and flow rate for coolants in each of the sections and various measuring signals such as control rod positions from the nuclear reactor. The simulator calculates the present power distribution before the control operation. The signals from the neutron detectors at each of the positions in the reactor core are estimated from the power distribution and errors are determined based on the estimated values and the measured values to determine the smooth error distribution in the axial direction. Then, input conditions at the time to be forecast are set by a data setter. The simulator calculates the forecast power distribution after the control operation based on the set conditions. The forecast power distribution is corrected using the error distribution. (Yoshino, Y.)

  15. Verification of ECMWF System 4 for seasonal hydrological forecasting in a northern climate

    Science.gov (United States)

    Bazile, Rachel; Boucher, Marie-Amélie; Perreault, Luc; Leconte, Robert

    2017-11-01

    Hydropower production requires optimal dam and reservoir management to prevent flooding damage and avoid operation losses. In a northern climate, where spring freshet constitutes the main inflow volume, seasonal forecasts can help to establish a yearly strategy. Long-term hydrological forecasts often rely on past observations of streamflow or meteorological data. Another alternative is to use ensemble meteorological forecasts produced by climate models. In this paper, those produced by the ECMWF (European Centre for Medium-Range Forecast) System 4 are examined and bias is characterized. Bias correction, through the linear scaling method, improves the performance of the raw ensemble meteorological forecasts in terms of continuous ranked probability score (CRPS). Then, three seasonal ensemble hydrological forecasting systems are compared: (1) the climatology of simulated streamflow, (2) the ensemble hydrological forecasts based on climatology (ESP) and (3) the hydrological forecasts based on bias-corrected ensemble meteorological forecasts from System 4 (corr-DSP). Simulated streamflow computed using observed meteorological data is used as benchmark. Accounting for initial conditions is valuable even for long-term forecasts. ESP and corr-DSP both outperform the climatology of simulated streamflow for lead times from 1 to 5 months depending on the season and watershed. Integrating information about future meteorological conditions also improves monthly volume forecasts. For the 1-month lead time, a gain exists for almost all watersheds during winter, summer and fall. However, volume forecasts performance for spring varies from one watershed to another. For most of them, the performance is close to the performance of ESP. For longer lead times, the CRPS skill score is mostly in favour of ESP, even if for many watersheds, ESP and corr-DSP have comparable skill. Corr-DSP appears quite reliable but, in some cases, under-dispersion or bias is observed. A more complex bias

  16. Reservoir Simulations of Low-Temperature Geothermal Reservoirs

    Science.gov (United States)

    Bedre, Madhur Ganesh

    The eastern United States generally has lower temperature gradients than the western United States. However, West Virginia, in particular, has higher temperature gradients compared to other eastern states. A recent study at Southern Methodist University by Blackwell et al. has shown the presence of a hot spot in the eastern part of West Virginia with temperatures reaching 150°C at a depth of between 4.5 and 5 km. This thesis work examines similar reservoirs at a depth of around 5 km resembling the geology of West Virginia, USA. The temperature gradients used are in accordance with the SMU study. In order to assess the effects of geothermal reservoir conditions on the lifetime of a low-temperature geothermal system, a sensitivity analysis study was performed on following seven natural and human-controlled parameters within a geothermal reservoir: reservoir temperature, injection fluid temperature, injection flow rate, porosity, rock thermal conductivity, water loss (%) and well spacing. This sensitivity analysis is completed by using ‘One factor at a time method (OFAT)’ and ‘Plackett-Burman design’ methods. The data used for this study was obtained by carrying out the reservoir simulations using TOUGH2 simulator. The second part of this work is to create a database of thermal potential and time-dependant reservoir conditions for low-temperature geothermal reservoirs by studying a number of possible scenarios. Variations in the parameters identified in sensitivity analysis study are used to expand the scope of database. Main results include the thermal potential of reservoir, pressure and temperature profile of the reservoir over its operational life (30 years for this study), the plant capacity and required pumping power. The results of this database will help the supply curves calculations for low-temperature geothermal reservoirs in the United States, which is the long term goal of the work being done by the geothermal research group under Dr. Anderson at

  17. Advancing reservoir operation description in physically based hydrological models

    Science.gov (United States)

    Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

    2016-04-01

    Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir

  18. Research on classified real-time flood forecasting framework based on K-means cluster and rough set.

    Science.gov (United States)

    Xu, Wei; Peng, Yong

    2015-01-01

    This research presents a new classified real-time flood forecasting framework. In this framework, historical floods are classified by a K-means cluster according to the spatial and temporal distribution of precipitation, the time variance of precipitation intensity and other hydrological factors. Based on the classified results, a rough set is used to extract the identification rules for real-time flood forecasting. Then, the parameters of different categories within the conceptual hydrological model are calibrated using a genetic algorithm. In real-time forecasting, the corresponding category of parameters is selected for flood forecasting according to the obtained flood information. This research tests the new classified framework on Guanyinge Reservoir and compares the framework with the traditional flood forecasting method. It finds that the performance of the new classified framework is significantly better in terms of accuracy. Furthermore, the framework can be considered in a catchment with fewer historical floods.

  19. Forecasting Hoabinh Reservoir’s Incoming Flow: An Application of Neural Networks with the Cuckoo Search Algorithm

    Directory of Open Access Journals (Sweden)

    Jeng-Fung Chen

    2014-11-01

    Full Text Available The accuracy of reservoir flow forecasting has the most significant influence on the assurance of stability and annual operations of hydro-constructions. For instance, accurate forecasting on the ebb and flow of Vietnam’s Hoabinh Reservoir can aid in the preparation and prevention of lowland flooding and drought, as well as regulating electric energy. This raises the need to propose a model that accurately forecasts the incoming flow of the Hoabinh Reservoir. In this study, a solution to this problem based on neural network with the Cuckoo Search (CS algorithm is presented. In particular, we used hydrographic data and predicted total incoming flows of the Hoabinh Reservoir over a period of 10 days. The Cuckoo Search algorithm was utilized to train the feedforward neural network (FNN for prediction. The algorithm optimized the weights between layers and biases of the neuron network. Different forecasting models for the three scenarios were developed. The constructed models have shown high forecasting performance based on the performance indices calculated. These results were also compared with those obtained from the neural networks trained by the particle swarm optimization (PSO and back-propagation (BP, indicating that the proposed approach performed more effectively. Based on the experimental results, the scenario using the rainfall and the flow as input yielded the highest forecasting accuracy when compared with other scenarios. The performance criteria RMSE, MAPE, and R obtained by the CS-FNN in this scenario were calculated as 48.7161, 0.067268 and 0.8965, respectively. These results were highly correlated to actual values. It is expected that this work may be useful for hydrographic forecasting.

  20. Developing a Seamless Hydrologic Forecast System: Integrating weather and climate prediction

    Science.gov (United States)

    Yuan, Xing; Wood, Eric; Liang, Miaoling

    2014-05-01

    Skilful and reliable forecasts of land surface hydrologic conditions from daily to seasonal scales will facilitate the management of reservoirs, agriculture and urban water resources, and provide early warning of flooding and droughts. With the improvement of numerical weather and climate predictions, dynamical model-based short-term or seasonal hydrologic forecasts have been widely implemented. However, limited dialogue exists between the hydrometeorological forecasting and the hydroclimate prediction communities. Given that the weather-climate prediction problem is seamless, and phenomena often occur at all time-scales, atmospheric scientists have been developing seamless prediction system in recent years using unified modeling systems to predict both weather and climate. Therefore, it is now time to develop seamless hydro-meteorological forecast systems that can provide forecast capability from flash flooding to seasonal droughts within a common system. Such a system would also allow one to investigate the interaction of hydroclimatic processes across scales and should enhance hydrologic predictability. In this presentation, several decades of 16-day reforecasts from NCEP's latest Global Forecast System (GFS) and 9-month reforecasts from its Climate Forecast System version 2 (CFSv2) will be used to investigate how the two-week weather forecast that has higher resolution and more observations in its data assimilation contributes to seasonal hydrologic predictability, and whether the seasonal climate forecast model that fully resolve the ocean-atmosphere-land coupling system is useful to extend the 1-2 week short-term hydrologic forecast up to 3-4 weeks. The Ohio basin in mid-western United States will be used as a case study.

  1. A review of reservoir desiltation

    DEFF Research Database (Denmark)

    Brandt, Anders

    2000-01-01

    physical geography, hydrology, desilation efficiency, reservoir flushing, density-current venting, sediment slucing, erosion pattern, downstream effects, flow characteristics, sedimentation......physical geography, hydrology, desilation efficiency, reservoir flushing, density-current venting, sediment slucing, erosion pattern, downstream effects, flow characteristics, sedimentation...

  2. Reservoir sedimentation; a literature survey

    NARCIS (Netherlands)

    Sloff, C.J.

    1991-01-01

    A survey of literature is made on reservoir sedimentation, one of the most threatening processes for world-wide reservoir performance. The sedimentation processes, their impacts, and their controlling factors are assessed from a hydraulic engineering point of view with special emphasis on

  3. FRACTURED PETROLEUM RESERVOIRS

    Energy Technology Data Exchange (ETDEWEB)

    Abbas Firoozabadi

    1999-06-11

    The four chapters that are described in this report cover a variety of subjects that not only give insight into the understanding of multiphase flow in fractured porous media, but they provide also major contribution towards the understanding of flow processes with in-situ phase formation. In the following, a summary of all the chapters will be provided. Chapter I addresses issues related to water injection in water-wet fractured porous media. There are two parts in this chapter. Part I covers extensive set of measurements for water injection in water-wet fractured porous media. Both single matrix block and multiple matrix blocks tests are covered. There are two major findings from these experiments: (1) co-current imbibition can be more efficient than counter-current imbibition due to lower residual oil saturation and higher oil mobility, and (2) tight fractured porous media can be more efficient than a permeable porous media when subjected to water injection. These findings are directly related to the type of tests one can perform in the laboratory and to decide on the fate of water injection in fractured reservoirs. Part II of Chapter I presents modeling of water injection in water-wet fractured media by modifying the Buckley-Leverett Theory. A major element of the new model is the multiplication of the transfer flux by the fractured saturation with a power of 1/2. This simple model can account for both co-current and counter-current imbibition and computationally it is very efficient. It can be orders of magnitude faster than a conventional dual-porosity model. Part II also presents the results of water injection tests in very tight rocks of some 0.01 md permeability. Oil recovery from water imbibition tests from such at tight rock can be as high as 25 percent. Chapter II discusses solution gas-drive for cold production from heavy-oil reservoirs. The impetus for this work is the study of new gas phase formation from in-situ process which can be significantly

  4. Reservoir engineering and hydrogeology

    International Nuclear Information System (INIS)

    Anon.

    1983-01-01

    Summaries are included which show advances in the following areas: fractured porous media, flow in single fractures or networks of fractures, hydrothermal flow, hydromechanical effects, hydrochemical processes, unsaturated-saturated systems, and multiphase multicomponent flows. The main thrust of these efforts is to understand the movement of mass and energy through rocks. This has involved treating fracture rock masses in which the flow phenomena within both the fractures and the matrix must be investigated. Studies also address the complex coupling between aspects of thermal, hydraulic, and mechanical processes associated with a nuclear waste repository in a fractured rock medium. In all these projects, both numerical modeling and simulation, as well as field studies, were employed. In the theoretical area, a basic understanding of multiphase flow, nonisothermal unsaturated behavior, and new numerical methods have been developed. The field work has involved reservoir testing, data analysis, and case histories at a number of geothermal projects

  5. Chalk as a reservoir

    DEFF Research Database (Denmark)

    Fabricius, Ida Lykke

    basin, so stylolite formation in the chalk is controlled by effective burial stress. The stylolites are zones of calcite dissolution and probably are the source of calcite for porefilling cementation which is typical in water zone chalk and also affect the reservoirs to different extent. The relatively...... 50% calcite, leaving the remaining internal surface to the fine grained silica and clay. The high specific surface of these components causes clay- and silica rich intervals to have high irreducible water saturation. Although chalks typically are found to be water wet, chalk with mixed wettability...... stabilizes chemically by recrystallization. This process requires energy and is promoted by temperature. This recrystallization in principle does not influence porosity, but only specific surface, which decreases during recrystallization, causing permeability to increase. The central North Sea is a warm...

  6. Pacifiers: a microbial reservoir.

    Science.gov (United States)

    Comina, Elodie; Marion, Karine; Renaud, François N R; Dore, Jeanne; Bergeron, Emmanuelle; Freney, Jean

    2006-12-01

    The permanent contact between the nipple part of pacifiers and the oral microflora offers ideal conditions for the development of biofilms. This study assessed the microbial contamination on the surface of 25 used pacifier nipples provided by day-care centers. Nine were made of silicone and 16 were made of latex. The biofilm was quantified using direct staining and microscopic observations followed by scraping and microorganism counting. The presence of a biofilm was confirmed on 80% of the pacifier nipples studied. This biofilm was mature for 36% of them. Latex pacifier nipples were more contaminated than silicone ones. The two main genera isolated were Staphylococcus and Candida. Our results confirm that nipples can be seen as potential reservoirs of infections. However, pacifiers do have some advantages; in particular, the potential protection they afford against sudden infant death syndrome. Strict rules of hygiene and an efficient antibiofilm cleaning protocol should be established to answer the worries of parents concerning the safety of pacifiers.

  7. Assessment of storm forecast

    DEFF Research Database (Denmark)

    Cutululis, Nicolaos Antonio; Hahmann, Andrea N.; Huus Bjerge, Martin

    at analysing the ability of existing forecast tools to predict storms at the Horns Rev 2 wind farm. The focus will be on predicting the time where the wind turbine will need to shut down to protect itself, e.g. the time where wind speed exceeds 25 m/s. At the same time, the planned shut-down should cost...... storms was analysed based on historical meteorological data available at Risø DTU and dynamically down-scaled to the Horns Rev 2 wind farm level. This solution was chosen due to the lack of measurements. Moreover, since the project started, there were four events during which Horns Rev 2 wind farm...

  8. Acid Fluid-Rock Interactions with Shales Comprising Unconventional Hydrocarbon Reservoirs and with Shale Capping Carbon Storage Reservoirs: Experimental Insights

    Science.gov (United States)

    Kaszuba, J. P.; Bratcher, J.; Marcon, V.; Herz-Thyhsen, R.

    2015-12-01

    Injection of HCl is often a first stage in the hydraulic fracturing process. These acidic fluids react with marls or shales in unconventional reservoirs, reactions generally comparable to reaction between shale caprocks and acidic, carbonated formation waters in a carbon storage reservoir. Hydrothermal experiments examine acid fluid-rock interaction with 1) an unconventional shale reservoir and 2) a model shale capping a carbon storage reservoir. In the former, unconventional reservoir rock and hydraulic fracturing fluid possessing a range of ionic strengths (I = 0.01, 0.15) and initial pH values (2.5 and 7.3) reacted at 115°C and 35 MPa for 28 days. In the latter, a model carbon storage reservoir (Fe-rich dolomite), shale caprock (illite), and shale-reservoir mixture each reacted with formation water (I = 0.1 and pH 6.3) at 160°C and 25 MPa for ~15 days. These three experiments were subsequently injected with sufficient CO2 to maintain CO2 saturation in the water and allowed to react for ~40 additional days. Acidic frac fluid was rapidly buffered (from pH 2.5 to 6.2 after 38 hrs) by reaction with reservoir rock whereas the pH of near-neutral frac fluid decreased (from 7.3 to 6.9) after 47 hrs. Carbonate dissolution released Ca and Sr into solution and feldspar dissolution released SiO2 and Li; the extent of reaction was greater in the experiment containing acidic frac fluid. All three carbon storage experiments displayed a similar pH decrease of 1.5 units after the addition of CO2. The pH remained low for the duration of the experiments because the immiscible supercritical CO2 phase provided an infinite reservoir of carbonic acid that could not be consumed by reaction with the rock. In all three experiments, Ca, Fe, Mg, Mn and SO4 increase with injection, but slowly decline through termination of the experiments. This trend suggests initial dissolution followed by re-precipitation of carbonates, which can be seen in modeling and SEM results. New clay minerals

  9. Advances in photonic reservoir computing

    Directory of Open Access Journals (Sweden)

    Van der Sande Guy

    2017-05-01

    Full Text Available We review a novel paradigm that has emerged in analogue neuromorphic optical computing. The goal is to implement a reservoir computer in optics, where information is encoded in the intensity and phase of the optical field. Reservoir computing is a bio-inspired approach especially suited for processing time-dependent information. The reservoir’s complex and high-dimensional transient response to the input signal is capable of universal computation. The reservoir does not need to be trained, which makes it very well suited for optics. As such, much of the promise of photonic reservoirs lies in their minimal hardware requirements, a tremendous advantage over other hardware-intensive neural network models. We review the two main approaches to optical reservoir computing: networks implemented with multiple discrete optical nodes and the continuous system of a single nonlinear device coupled to delayed feedback.

  10. Enhanced heavy oil recovery for carbonate reservoirs integrating cross-well seismic–a synthetic Wafra case study

    KAUST Repository

    Katterbauer, Klemens

    2015-07-14

    Heavy oil recovery has been a major focus in the oil and gas industry to counter the rapid depletion of conventional reservoirs. Various techniques for enhancing the recovery of heavy oil were developed and pilot-tested, with steam drive techniques proven in most circumstances to be successful and economically viable. The Wafra field in Saudi Arabia is at the forefront of utilizing steam recovery for carbonate heavy oil reservoirs in the Middle East. With growing injection volumes, tracking the steam evolution within the reservoir and characterizing the formation, especially in terms of its porosity and permeability heterogeneity, are key objectives for sound economic decisions and enhanced production forecasts. We have developed an integrated reservoir history matching framework using ensemble based techniques incorporating seismic data for enhancing reservoir characterization and improving history matches. Examining the performance on a synthetic field study of the Wafra field, we could demonstrate the improved characterization of the reservoir formation, determining more accurately the position of the steam chambers and obtaining more reliable forecasts of the reservoir’s recovery potential. History matching results are fairly robust even for noise levels up to 30%. The results demonstrate the potential of the integration of full-waveform seismic data for steam drive reservoir characterization and increased recovery efficiency.

  11. A Novel Integrated Approach to Modelling of Depletion-Induced Change in Full Permeability Tensor of Naturally Fractured Reservoirs

    Directory of Open Access Journals (Sweden)

    Zahra Izadi

    2014-12-01

    Full Text Available More than half of all hydrocarbon reservoirs are Naturally Fractured Reservoirs (NFRs, in which production forecasting is a complicated function of fluid flow in a fracture-matrix system. Modelling of fluid flow in NFRs is challenging due to formation heterogeneity and anisotropy. Stress sensitivity and depletion effect on already-complex reservoir permeability add to the sophistication. Horizontal permeability anisotropy and stress sensitivity are often ignored or inaccurately taken into account when simulating fluid flow in NFRs. The aim of this paper is to present an integrated approach for evaluating the dynamic and true anisotropic nature of permeability in naturally fractured reservoirs. Among other features, this approach considers the effect of reservoir depletion on reservoir permeability tensor, allowing more realistic production forecasts. In this approach the NFR is discretized into grids for which an analytical model yields full permeability tensors. Then, fluid flow is modelled using the finite-element method to obtain pore-pressure distribution within the reservoir. Next, another analytical model evaluates the change in the aperture of individual fractures as a function of effective stress and rock mechanical properties. The permeability tensor of each grid is then updated based on the apertures obtained for the current time step. The integrated model proceeds according to the next prescribed time increments.

  12. Gravity observations for hydrocarbon reservoir monitoring

    NARCIS (Netherlands)

    Glegola, M.A.

    2013-01-01

    In this thesis the added value of gravity observations for hydrocarbon reservoir monitoring and characterization is investigated. Reservoir processes and reservoir types most suitable for gravimetric monitoring are identified. Major noise sources affecting time-lapse gravimetry are analyzed. The

  13. Heat Extraction Project, geothermal reservoir engineering research at Stanford. Fourth annual report, January 1, 1988--December 1, 1988

    Energy Technology Data Exchange (ETDEWEB)

    Kruger, P.

    1989-01-01

    The main objective of the SGP Heat Extraction Project is to provide a means for estimating the thermal behavior of geothermal fluids produced from fractured hydrothermal resources. The methods are based on estimated thermal properties of the reservoir components, reservoir management planning of production and reinjection, and the mixing of reservoir fluids: geothermal, resource fluid cooled by drawdown and infiltrating groundwater, and reinjected recharge heated by sweep flow through the reservoir formation. Several reports and publications, listed in Appendix A, describe the development of the analytical methods which were part of five Engineer and PhD dissertations, and the results from many applications of the methods to achieve the project objectives. The Heat Extraction Project is to evaluate the thermal properties of fractured geothermal resource and forecasted effects of reinjection recharge into operating reservoirs.

  14. Deep Learning Based Solar Flare Forecasting Model. I. Results for Line-of-sight Magnetograms

    Science.gov (United States)

    Huang, Xin; Wang, Huaning; Xu, Long; Liu, Jinfu; Li, Rong; Dai, Xinghua

    2018-03-01

    Solar flares originate from the release of the energy stored in the magnetic field of solar active regions, the triggering mechanism for these flares, however, remains unknown. For this reason, the conventional solar flare forecast is essentially based on the statistic relationship between solar flares and measures extracted from observational data. In the current work, the deep learning method is applied to set up the solar flare forecasting model, in which forecasting patterns can be learned from line-of-sight magnetograms of solar active regions. In order to obtain a large amount of observational data to train the forecasting model and test its performance, a data set is created from line-of-sight magnetogarms of active regions observed by SOHO/MDI and SDO/HMI from 1996 April to 2015 October and corresponding soft X-ray solar flares observed by GOES. The testing results of the forecasting model indicate that (1) the forecasting patterns can be automatically reached with the MDI data and they can also be applied to the HMI data; furthermore, these forecasting patterns are robust to the noise in the observational data; (2) the performance of the deep learning forecasting model is not sensitive to the given forecasting periods (6, 12, 24, or 48 hr); (3) the performance of the proposed forecasting model is comparable to that of the state-of-the-art flare forecasting models, even if the duration of the total magnetograms continuously spans 19.5 years. Case analyses demonstrate that the deep learning based solar flare forecasting model pays attention to areas with the magnetic polarity-inversion line or the strong magnetic field in magnetograms of active regions.

  15. Analysis of real-time reservoir monitoring : reservoirs, strategies, & modeling.

    Energy Technology Data Exchange (ETDEWEB)

    Mani, Seethambal S.; van Bloemen Waanders, Bart Gustaaf; Cooper, Scott Patrick; Jakaboski, Blake Elaine; Normann, Randy Allen; Jennings, Jim (University of Texas at Austin, Austin, TX); Gilbert, Bob (University of Texas at Austin, Austin, TX); Lake, Larry W. (University of Texas at Austin, Austin, TX); Weiss, Chester Joseph; Lorenz, John Clay; Elbring, Gregory Jay; Wheeler, Mary Fanett (University of Texas at Austin, Austin, TX); Thomas, Sunil G. (University of Texas at Austin, Austin, TX); Rightley, Michael J.; Rodriguez, Adolfo (University of Texas at Austin, Austin, TX); Klie, Hector (University of Texas at Austin, Austin, TX); Banchs, Rafael (University of Texas at Austin, Austin, TX); Nunez, Emilio J. (University of Texas at Austin, Austin, TX); Jablonowski, Chris (University of Texas at Austin, Austin, TX)

    2006-11-01

    The project objective was to detail better ways to assess and exploit intelligent oil and gas field information through improved modeling, sensor technology, and process control to increase ultimate recovery of domestic hydrocarbons. To meet this objective we investigated the use of permanent downhole sensors systems (Smart Wells) whose data is fed real-time into computational reservoir models that are integrated with optimized production control systems. The project utilized a three-pronged approach (1) a value of information analysis to address the economic advantages, (2) reservoir simulation modeling and control optimization to prove the capability, and (3) evaluation of new generation sensor packaging to survive the borehole environment for long periods of time. The Value of Information (VOI) decision tree method was developed and used to assess the economic advantage of using the proposed technology; the VOI demonstrated the increased subsurface resolution through additional sensor data. Our findings show that the VOI studies are a practical means of ascertaining the value associated with a technology, in this case application of sensors to production. The procedure acknowledges the uncertainty in predictions but nevertheless assigns monetary value to the predictions. The best aspect of the procedure is that it builds consensus within interdisciplinary teams The reservoir simulation and modeling aspect of the project was developed to show the capability of exploiting sensor information both for reservoir characterization and to optimize control of the production system. Our findings indicate history matching is improved as more information is added to the objective function, clearly indicating that sensor information can help in reducing the uncertainty associated with reservoir characterization. Additional findings and approaches used are described in detail within the report. The next generation sensors aspect of the project evaluated sensors and packaging

  16. Climate Forecast System Version 2 (CFSv2) Operational Forecasts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Climate Forecast System Version 2 (CFSv2) produced by the NOAA National Centers for Environmental Prediction (NCEP) is a fully coupled model representing the...

  17. A stochastic approach to the operative control of flood flows through a reservoir

    Directory of Open Access Journals (Sweden)

    Jaroš Lubomír

    2016-03-01

    Full Text Available The contribution focuses on the design of a control algorithm aimed at the operative control of runoff water from a reservoir during flood situations. Management is based on the stochastically specified forecast of water inflow into the reservoir. From a mathematical perspective, the solved task presents the control of a dynamic system whose predicted hydrological input (water inflow is characterised by significant uncertainty. The algorithm uses a combination of simulation model data, in which the position of the bottom outlets is sought via nonlinear optimisation methods, and artificial intelligence methods (adaptation and fuzzy model. The task is written in the technical computing language MATLAB using the Fuzzy Logic Toolbox.

  18. Black Sea coastal forecasting system

    Directory of Open Access Journals (Sweden)

    A. I. Kubryakov

    2012-03-01

    Full Text Available The Black Sea coastal nowcasting and forecasting system was built within the framework of EU FP6 ECOOP (European COastalshelf sea OPerational observing and forecasting system project for five regions: the south-western basin along the coasts of Bulgaria and Turkey, the north-western shelf along the Romanian and Ukrainian coasts, coastal zone around of the Crimea peninsula, the north-eastern Russian coastal zone and the coastal zone of Georgia. The system operates in the real-time mode during the ECOOP project and afterwards. The forecasts include temperature, salinity and current velocity fields. Ecosystem model operates in the off-line mode near the Crimea coast.

  19. Forecasts: uncertain, inaccurate and biased?

    DEFF Research Database (Denmark)

    Nicolaisen, Morten Skou; Ambrasaite, Inga; Salling, Kim Bang

    2012-01-01

    Cost Benefit Analysis (CBA) is the dominating methodology for appraisal of transport infrastructure projects across the globe. In order to adequately assess the costs and benefits of such projects two types of forecasts are crucial to the validity of the appraisal. First are the forecasts of cons....... It is recommended that more attention is given to monitoring completed projects so future forecasts can benefit from better data availability through systematic ex-post evaluations, and an example of how to utilize such data in practice is presented....

  20. Assessing Seasonal Climate Forecasts over Africa to Support Decision-Making : Bridging Science and Policy Implication for Managing Climate Extremes

    NARCIS (Netherlands)

    Wanders, Niko|info:eu-repo/dai/nl/364253940; Wood, Eric F.

    2018-01-01

    Recent drought events like in the 2011 Horn of Africa and the ongoing drought in California have an enormous impact on nature and society. Reliable seasonal weather outlooks are critical for drought management and other applications like, crop modelling, flood forecasting and planning of reservoir

  1. Analysis of formation pressure test results in the Mount Elbert methane hydrate reservoir through numerical simulation

    Science.gov (United States)

    Kurihara, M.; Sato, A.; Funatsu, K.; Ouchi, H.; Masuda, Y.; Narita, H.; Collett, T.S.

    2011-01-01

    Targeting the methane hydrate (MH) bearing units C and D at the Mount Elbert prospect on the Alaska North Slope, four MDT (Modular Dynamic Formation Tester) tests were conducted in February 2007. The C2 MDT test was selected for history matching simulation in the MH Simulator Code Comparison Study. Through history matching simulation, the physical and chemical properties of the unit C were adjusted, which suggested the most likely reservoir properties of this unit. Based on these properties thus tuned, the numerical models replicating "Mount Elbert C2 zone like reservoir" "PBU L-Pad like reservoir" and "PBU L-Pad down dip like reservoir" were constructed. The long term production performances of wells in these reservoirs were then forecasted assuming the MH dissociation and production by the methods of depressurization, combination of depressurization and wellbore heating, and hot water huff and puff. The predicted cumulative gas production ranges from 2.16??106m3/well to 8.22??108m3/well depending mainly on the initial temperature of the reservoir and on the production method.This paper describes the details of modeling and history matching simulation. This paper also presents the results of the examinations on the effects of reservoir properties on MH dissociation and production performances under the application of the depressurization and thermal methods. ?? 2010 Elsevier Ltd.

  2. Review on applications of artificial intelligence methods for dam and reservoir-hydro-environment models.

    Science.gov (United States)

    Allawi, Mohammed Falah; Jaafar, Othman; Mohamad Hamzah, Firdaus; Abdullah, Sharifah Mastura Syed; El-Shafie, Ahmed

    2018-04-03

    Efficacious operation for dam and reservoir system could guarantee not only a defenselessness policy against natural hazard but also identify rule to meet the water demand. Successful operation of dam and reservoir systems to ensure optimal use of water resources could be unattainable without accurate and reliable simulation models. According to the highly stochastic nature of hydrologic parameters, developing accurate predictive model that efficiently mimic such a complex pattern is an increasing domain of research. During the last two decades, artificial intelligence (AI) techniques have been significantly utilized for attaining a robust modeling to handle different stochastic hydrological parameters. AI techniques have also shown considerable progress in finding optimal rules for reservoir operation. This review research explores the history of developing AI in reservoir inflow forecasting and prediction of evaporation from a reservoir as the major components of the reservoir simulation. In addition, critical assessment of the advantages and disadvantages of integrated AI simulation methods with optimization methods has been reported. Future research on the potential of utilizing new innovative methods based AI techniques for reservoir simulation and optimization models have also been discussed. Finally, proposal for the new mathematical procedure to accomplish the realistic evaluation of the whole optimization model performance (reliability, resilience, and vulnerability indices) has been recommended.

  3. Sediment Characteristics of Tennessee Streams and Reservoirs

    National Research Council Canada - National Science Library

    Trimble, Stanley W; Carey, William P

    1984-01-01

    Suspended-sediment and reservoir sedimentation data have been analyzed to determine sediment yields and transport characteristics of Tennessee streams Data from 31 reservoirs plus suspended-sediment...

  4. Changes to the Bakomi Reservoir

    Directory of Open Access Journals (Sweden)

    Kubinský Daniel

    2014-08-01

    Full Text Available This article is focused on the analysis and evaluation of the changes of the bottom of the Bakomi reservoir, the total volume of the reservoir, ecosystems, as well as changes in the riparian zone of the Bakomi reservoir (situated in the central Slovakia. Changes of the water component of the reservoir were subject to the deposition by erosion-sedimentation processes, and were identifed on the basis of a comparison of the present relief of the bottom of reservoir obtained from feld measurements (in 2011 with the relief measurements of the bottom obtained from the 1971 historical maps, (i.e. over a period of 40 years. Changes of landscape structures of the riparian zone have been mapped for the time period of 1949–2013; these changes have been identifed with the analysis of ortophotomaps and the feld survey. There has been a signifcant rise of disturbed shores with low herb grassland. Over a period of 40 years, there has been a deposition of 667 m3 of sediments. The results showed that there were no signifcant changes in the local ecosystems of the Bakomi reservoir in comparison to the other reservoirs in the vicinity of Banská Štiavnica.

  5. TRITIUM RESERVOIR STRUCTURAL PERFORMANCE PREDICTION

    Energy Technology Data Exchange (ETDEWEB)

    Lam, P.S.; Morgan, M.J

    2005-11-10

    The burst test is used to assess the material performance of tritium reservoirs in the surveillance program in which reservoirs have been in service for extended periods of time. A materials system model and finite element procedure were developed under a Savannah River Site Plant-Directed Research and Development (PDRD) program to predict the structural response under a full range of loading and aged material conditions of the reservoir. The results show that the predicted burst pressure and volume ductility are in good agreement with the actual burst test results for the unexposed units. The material tensile properties used in the calculations were obtained from a curved tensile specimen harvested from a companion reservoir by Electric Discharge Machining (EDM). In the absence of exposed and aged material tensile data, literature data were used for demonstrating the methodology in terms of the helium-3 concentration in the metal and the depth of penetration in the reservoir sidewall. It can be shown that the volume ductility decreases significantly with the presence of tritium and its decay product, helium-3, in the metal, as was observed in the laboratory-controlled burst tests. The model and analytical procedure provides a predictive tool for reservoir structural integrity under aging conditions. It is recommended that benchmark tests and analysis for aged materials be performed. The methodology can be augmented to predict performance for reservoir with flaws.

  6. Earthquake number forecasts testing

    Science.gov (United States)

    Kagan, Yan Y.

    2017-10-01

    We study the distributions of earthquake numbers in two global earthquake catalogues: Global Centroid-Moment Tensor and Preliminary Determinations of Epicenters. The properties of these distributions are especially required to develop the number test for our forecasts of future seismic activity rate, tested by the Collaboratory for Study of Earthquake Predictability (CSEP). A common assumption, as used in the CSEP tests, is that the numbers are described by the Poisson distribution. It is clear, however, that the Poisson assumption for the earthquake number distribution is incorrect, especially for the catalogues with a lower magnitude threshold. In contrast to the one-parameter Poisson distribution so widely used to describe earthquake occurrences, the negative-binomial distribution (NBD) has two parameters. The second parameter can be used to characterize the clustering or overdispersion of a process. We also introduce and study a more complex three-parameter beta negative-binomial distribution. We investigate the dependence of parameters for both Poisson and NBD distributions on the catalogue magnitude threshold and on temporal subdivision of catalogue duration. First, we study whether the Poisson law can be statistically rejected for various catalogue subdivisions. We find that for most cases of interest, the Poisson distribution can be shown to be rejected statistically at a high significance level in favour of the NBD. Thereafter, we investigate whether these distributions fit the observed distributions of seismicity. For this purpose, we study upper statistical moments of earthquake numbers (skewness and kurtosis) and compare them to the theoretical values for both distributions. Empirical values for the skewness and the kurtosis increase for the smaller magnitude threshold and increase with even greater intensity for small temporal subdivision of catalogues. The Poisson distribution for large rate values approaches the Gaussian law, therefore its skewness

  7. A reservoir simulation approach for modeling of naturally fractured reservoirs

    Directory of Open Access Journals (Sweden)

    H. Mohammadi

    2012-12-01

    Full Text Available In this investigation, the Warren and Root model proposed for the simulation of naturally fractured reservoir was improved. A reservoir simulation approach was used to develop a 2D model of a synthetic oil reservoir. Main rock properties of each gridblock were defined for two different types of gridblocks called matrix and fracture gridblocks. These two gridblocks were different in porosity and permeability values which were higher for fracture gridblocks compared to the matrix gridblocks. This model was solved using the implicit finite difference method. Results showed an improvement in the Warren and Root model especially in region 2 of the semilog plot of pressure drop versus time, which indicated a linear transition zone with no inflection point as predicted by other investigators. Effects of fracture spacing, fracture permeability, fracture porosity, matrix permeability and matrix porosity on the behavior of a typical naturally fractured reservoir were also presented.

  8. Evaluating Atlantic tropical cyclone track error distributions for use in probabilistic forecasts of wind distribution

    OpenAIRE

    Neese, Jay M.

    2010-01-01

    Approved for public release; distribution is unlimited This thesis investigates whether the National Hurricane Center (NHC) operational product for producing probabilistic forecasts of tropical cyclone (TC) wind distributions could be further improved by examining the distributions of track errors it draws upon to calculate probabilities. The track spread/skill relationship for several global ensemble prediction system forecasts is examined as a condition for a description of a full p...

  9. Hierarchical Estimation as Basis for Hierarchical Forecasting

    NARCIS (Netherlands)

    Strijbosch, L.W.G.; Heuts, R.M.J.; Moors, J.J.A.

    2006-01-01

    In inventory management, hierarchical forecasting (HF) is a hot issue : families of items are formed for which total demand is forecasted; total forecast then is broken up to produce forecasts for the individual items.Since HF is a complicated procedure, analytical results are hard to obtain;

  10. Recurrent networks for wave forecasting

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    The tremendous increase in offshore operational activities demands improved wave forecasting techniques. With the knowledge of accurate wave conditions, it is possible to carry out the marine activities such as offshore drilling, naval operations...

  11. Load forecasting of supermarket refrigeration

    DEFF Research Database (Denmark)

    Rasmussen, Lisa Buth; Bacher, Peder; Madsen, Henrik

    2016-01-01

    This paper presents a novel study of models for forecasting the electrical load for supermarket refrigeration. The data used for building the models consists of load measurements, local climate measurements and weather forecasts. The load measurements are from a supermarket located in a village...... in Denmark. Every hour the hourly electrical load for refrigeration is forecasted for the following 42 h. The forecast models are adaptive linear time series models. The model has two regimes; one for opening hours and one for closing hours, this is modeled by a regime switching model and two different...... methods for predicting the regimes are tested. The dynamic relation between the weather and the load is modeled by simple transfer functions and the non-linearities are described using spline functions. The results are thoroughly evaluated and it is shown that the spline functions are suitable...

  12. Forecasting and management of technology

    National Research Council Canada - National Science Library

    Roper, A. T

    2011-01-01

    .... The scope of this edition has broadened to include management of technology content that is relevant to now to executives in organizations while updating and strengthening the technology forecasting...

  13. THE SURDUC RESERVOIR (ROMANIA

    Directory of Open Access Journals (Sweden)

    Niculae Iulian TEODORESCU

    2008-06-01

    Full Text Available The Surduc reservoir was projected to ensure more water when water is scarce and to thus provide especially the city Timisoara, downstream of it with water.The accumulation is placed on the main affluent of the Bega river, Gladna in the upper part of its watercourse.The dam behind which this accumulation was created is of a frontal type made of enrochements with a masque made of armed concrete on the upstream part and protected/sustained by grass on the downstream. The dam is 130m long on its coping and a constructed height of 34 m. It is also endowed with spillway for high water and two bottom outlets formed of two conduits, at the end of which is the microplant. The second part of my paper deals with the hydrometric analysis of the Accumulation Surduc and its impact upon the flow, especially the maximum run-off. This influence is exemplified through the high flood from the 29th of July 1980, the most significant flood recorded in the basin with an apparition probability of 0.002%.

  14. Targeted electrohydrodynamic printing for micro-reservoir drug delivery systems

    International Nuclear Information System (INIS)

    Hwang, Tae Heon; Kim, Jin Bum; Yang, Da Som; Ryu, WonHyoung; Park, Yong-il

    2013-01-01

    Microfluidic drug delivery systems consisting of a drug reservoir and microfluidic channels have shown the possibility of simple and robust modulation of drug release rate. However, the difficulty of loading a small quantity of drug into drug reservoirs at a micro-scale limited further development of such systems. Electrohydrodynamic (EHD) printing was employed to fill micro-reservoirs with controlled amount of drugs in the range of a few hundreds of picograms to tens of micrograms with spatial resolution of as small as 20 µm. Unlike most EHD systems, this system was configured in combination with an inverted microscope that allows in situ targeting of drug loading at micrometer scale accuracy. Methylene blue and rhodamine B were used as model drugs in distilled water, isopropanol and a polymer solution of a biodegradable polymer and dimethyl sulfoxide (DMSO). Also tetracycline-HCl/DI water was used as actual drug ink. The optimal parameters of EHD printing to load an extremely small quantity of drug into microscale drug reservoirs were investigated by changing pumping rates, the strength of an electric field and drug concentration. This targeted EHD technique was used to load drugs into the microreservoirs of PDMS microfluidic drug delivery devices and their drug release performance was demonstrated in vitro. (paper)

  15. Measuring inaccuracy in travel demand forecasting

    DEFF Research Database (Denmark)

    Flyvbjerg, Bent

    2005-01-01

    Project promoters, forecasters, and managers sometimes object to two things in measuring inaccuracy in travel demand forecasting: (1)using the forecast made at the time of making the decision to build as the basis for measuring inaccuracy and (2)using traffic during the first year of operations...... in travel demand forecasts are likely to be conservatively biased, i.e., accuracy in travel demand forecasts estimated from such samples would likely be higher than accuracy in travel demand forecasts in the project population. This bias must be taken into account when interpreting the results from...... statistical analyses of inaccuracy in travel demand forecasting....

  16. Stagnation pressure activated fuel release mechanism for hypersonic projectiles

    Science.gov (United States)

    Cartland, Harry E.; Hunter, John W.

    2003-01-01

    A propulsion-assisted projectile has a body, a cowl forming a combustion section and a nozzle section. The body has a fuel reservoir within a central portion of the body, and a fuel activation system located along the central axis of the body and having a portion of the fuel activation system within the fuel reservoir. The fuel activation system has a fuel release piston with a forward sealing member where the fuel release piston is adapted to be moved when the forward sealing member is impacted with an air flow, and an air-flow channel adapted to conduct ambient air during flight to the fuel release piston.

  17. Forecasting with Dynamic Regression Models

    CERN Document Server

    Pankratz, Alan

    2012-01-01

    One of the most widely used tools in statistical forecasting, single equation regression models is examined here. A companion to the author's earlier work, Forecasting with Univariate Box-Jenkins Models: Concepts and Cases, the present text pulls together recent time series ideas and gives special attention to possible intertemporal patterns, distributed lag responses of output to input series and the auto correlation patterns of regression disturbance. It also includes six case studies.

  18. Forecasting Interest Rates and Inflation

    DEFF Research Database (Denmark)

    Chun, Albert Lee

    This study examines the performance of the professional analysts in the Blue Chip Financial Forecasts vis-à-vis set of competing econometric benchmarks, including shrinkage versions that adjust for in-sample over-fit in improving out-of-sample performance. The individual participants perform...... document predictability in the survey forecast errors, which exhibit substantial variability across different economic episodes, and propose a new adjustment that can substantially improve the performance of the survey participants....

  19. Lava lake level as a gauge of magma reservoir pressure and eruptive hazard

    Science.gov (United States)

    Patrick, Matthew R.; Anderson, Kyle R.; Poland, Michael P.; Orr, Tim R.; Swanson, Donald A.

    2015-01-01

    Forecasting volcanic activity relies fundamentally on tracking magma pressure through the use of proxies, such as ground surface deformation and earthquake rates. Lava lakes at open-vent basaltic volcanoes provide a window into the uppermost magma system for gauging reservoir pressure changes more directly. At Kīlauea Volcano (Hawaiʻi, USA) the surface height of the summit lava lake in Halemaʻumaʻu Crater fluctuates with surface deformation over short (hours to days) and long (weeks to months) time scales. This correlation implies that the lake behaves as a simple piezometer of the subsurface magma reservoir. Changes in lava level and summit deformation scale with (and shortly precede) changes in eruption rate from Kīlauea's East Rift Zone, indicating that summit lava level can be used for short-term forecasting of rift zone activity and associated hazards at Kīlauea.

  20. Evaluation of Ensemble Water Supply and Demands Forecasts for Water Management in the Klamath River Basin

    Science.gov (United States)

    Broman, D.; Gangopadhyay, S.; McGuire, M.; Wood, A.; Leady, Z.; Tansey, M. K.; Nelson, K.; Dahm, K.

    2017-12-01

    The Upper Klamath River Basin in south central Oregon and north central California is home to the Klamath Irrigation Project, which is operated by the Bureau of Reclamation and provides water to around 200,000 acres of agricultural lands. The project is managed in consideration of not only water deliveries to irrigators, but also wildlife refuge water demands, biological opinion requirements for Endangered Species Act (ESA) listed fish, and Tribal Trust responsibilities. Climate change has the potential to impact water management in terms of volume and timing of water and the ability to meet multiple objectives. Current operations use a spreadsheet-based decision support tool, with water supply forecasts from the National Resources Conservation Service (NRCS) and California-Nevada River Forecast Center (CNRFC). This tool is currently limited in its ability to incorporate in ensemble forecasts, which offer the potential for improved operations by quantifying forecast uncertainty. To address these limitations, this study has worked to develop a RiverWare based water resource systems model, flexible enough to use across multiple decision time-scales, from short-term operations out to long-range planning. Systems model development has been accompanied by operational system development to handle data management and multiple modeling components. Using a set of ensemble hindcasts, this study seeks to answer several questions: A) Do a new set of ensemble streamflow forecasts have additional skill beyond what?, and allow for improved decision making under changing conditions? B) Do net irrigation water requirement forecasts developed in this project to quantify agricultural demands and reservoir evaporation forecasts provide additional benefits to decision making beyond water supply forecasts? C) What benefit do ensemble forecasts have in the context of water management decisions?